AI_NSF.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e64ce553",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Test of simple scraper and entity extractor.\n",
    "import requests\n",
    "import datetime\n",
    "# import packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests\n",
    "from pandas.io.json import json_normalize #special package in pandas\n",
    "import json\n",
    "from matplotlib.pyplot import *\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c66b4442",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type(awards): <class 'dict'>\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: AMHERST\n",
      "awardeeName: SUNY at Buffalo\n",
      "awardeeStateCode: NY\n",
      "fundsObligatedAmt: 10000000\n",
      "id: 2229873\n",
      "piFirstName: Venugopal\n",
      "piLastName: Govindaraju\n",
      "publicAccessMandate: 1\n",
      "date: 01/06/2023\n",
      "title: AI Institute for Transforming Education for Children with Speech and Language Processing Challenges\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: BALTIMORE\n",
      "awardeeName: University of Maryland Baltimore County\n",
      "awardeeStateCode: MD\n",
      "fundsObligatedAmt: 160000\n",
      "id: 2309760\n",
      "piFirstName: Houbing\n",
      "piLastName: Song\n",
      "publicAccessMandate: 1\n",
      "date: 12/13/2022\n",
      "title: Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: ATLANTA\n",
      "awardeeName: Georgia Tech Research Corporation\n",
      "awardeeStateCode: GA\n",
      "fundsObligatedAmt: 7059902\n",
      "id: 2247790\n",
      "piFirstName: Ashok\n",
      "piLastName: Goel\n",
      "publicAccessMandate: 1\n",
      "date: 10/27/2022\n",
      "title: AI Institute for Adult Learning and Online Education (ALOE)\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: ATLANTA\n",
      "awardeeName: Georgia Tech Research Corporation\n",
      "awardeeStateCode: GA\n",
      "fundsObligatedAmt: 800000\n",
      "id: 2205152\n",
      "piFirstName: Ali\n",
      "piLastName: Adibi\n",
      "publicAccessMandate: 1\n",
      "date: 09/13/2022\n",
      "title: SCH: Intelligent Radiology Through Human-Machine Cooperation\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: CORONA\n",
      "awardeeName: New York Hall of Science\n",
      "awardeeStateCode: NY\n",
      "fundsObligatedAmt: 74971\n",
      "id: 2230850\n",
      "piFirstName: Dorothy\n",
      "piLastName: Bennett\n",
      "publicAccessMandate: 1\n",
      "date: 08/31/2022\n",
      "title: Conference on Human-Centered Approaches to Artificial Intelligence Literacy in Informal Learning\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: EUGENE\n",
      "awardeeName: University of Oregon Eugene\n",
      "awardeeStateCode: OR\n",
      "fundsObligatedAmt: 299920\n",
      "id: 2225949\n",
      "piFirstName: Lei\n",
      "piLastName: Jiao\n",
      "publicAccessMandate: 1\n",
      "date: 08/30/2022\n",
      "title: Collaborative Research: CNS Core: Small: Edge AI with Streaming Data: Algorithmic Foundations for Online Learning and Control\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: WEST LAFAYETTE\n",
      "awardeeName: Purdue University\n",
      "awardeeStateCode: IN\n",
      "fundsObligatedAmt: 300000\n",
      "id: 2225950\n",
      "piFirstName: Xiaojun\n",
      "piLastName: Lin\n",
      "publicAccessMandate: 1\n",
      "date: 08/30/2022\n",
      "title: Collaborative Research: CNS Core: Small: Edge AI with Streaming Data: Algorithmic Foundations for Online Learning and Control\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: CLEMSON\n",
      "awardeeName: Clemson University\n",
      "awardeeStateCode: SC\n",
      "fundsObligatedAmt: 600000\n",
      "id: 2232690\n",
      "piFirstName: Kelly\n",
      "piLastName: Caine\n",
      "publicAccessMandate: 1\n",
      "date: 08/29/2022\n",
      "title: CICI: UCSS: Maximizing Data Utility and Participant Privacy through Usable, Secure Data Workflows for Human-Centered AI Research\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: NOTRE DAME\n",
      "awardeeName: University of Notre Dame\n",
      "awardeeStateCode: IN\n",
      "fundsObligatedAmt: 150000\n",
      "id: 2222751\n",
      "piFirstName: Yongsuk\n",
      "piLastName: Lee\n",
      "publicAccessMandate: 1\n",
      "date: 08/26/2022\n",
      "title: FW-HTF-P: Transforming Small and Medium-Sized Manufacturing Firms Through Participatory AI Adoption and Implementation\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: PITTSBURGH\n",
      "awardeeName: Carnegie-Mellon University\n",
      "awardeeStateCode: PA\n",
      "fundsObligatedAmt: 790631\n",
      "id: 2211882\n",
      "piFirstName: Tianqi\n",
      "piLastName: Chen\n",
      "publicAccessMandate: 1\n",
      "date: 08/22/2022\n",
      "title: CNS: Medium: Ground up Adaptive Learning System for Heterogeneous Environments\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: DAYTONA BEACH\n",
      "awardeeName: Embry-Riddle Aeronautical University\n",
      "awardeeStateCode: FL\n",
      "fundsObligatedAmt: 0\n",
      "id: 2229975\n",
      "piFirstName: Houbing\n",
      "piLastName: Song\n",
      "publicAccessMandate: 1\n",
      "date: 08/18/2022\n",
      "title: Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: ATLANTA\n",
      "awardeeName: Georgia Tech Research Corporation\n",
      "awardeeStateCode: GA\n",
      "fundsObligatedAmt: 1726706\n",
      "id: 2214463\n",
      "piFirstName: Brian\n",
      "piLastName: Magerko\n",
      "publicAccessMandate: 1\n",
      "date: 08/15/2022\n",
      "title: Fostering AI Literacy through Embodiment and Creativity across Informal Learning Spaces\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: MOBILE\n",
      "awardeeName: University of South Alabama\n",
      "awardeeStateCode: AL\n",
      "fundsObligatedAmt: 3006595\n",
      "id: 2218046\n",
      "piFirstName: Na\n",
      "piLastName: Gong\n",
      "publicAccessMandate: 1\n",
      "date: 08/01/2022\n",
      "title: RII Track 2 FEC: Building Research Infrastructure and Workforce in Edge Artificial Intelligence\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: BOSTON\n",
      "awardeeName: Northeastern University\n",
      "awardeeStateCode: MA\n",
      "fundsObligatedAmt: 299375\n",
      "id: 2147220\n",
      "piFirstName: Ronald\n",
      "piLastName: Sandler\n",
      "publicAccessMandate: 1\n",
      "date: 07/07/2022\n",
      "title: Research Community Development Grant: Summer Training Program to Expand the Al and Data Ethics Research Community\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: DAVIS\n",
      "awardeeName: University of California-Davis\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 905224\n",
      "id: 2231251\n",
      "piFirstName: Stephen\n",
      "piLastName: Brown\n",
      "publicAccessMandate: 1\n",
      "date: 06/28/2022\n",
      "title: AI Institutes Leadership Summit and Development of a Virtual Organization\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: LA JOLLA\n",
      "awardeeName: University of California-San Diego\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 405000\n",
      "id: 2150643\n",
      "piFirstName: Garrison\n",
      "piLastName: Cottrell\n",
      "publicAccessMandate: 1\n",
      "date: 06/24/2022\n",
      "title: REU Site: Interdisciplinary AI Research for Undergraduates\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: URBANA\n",
      "awardeeName: University of Illinois at Urbana-Champaign\n",
      "awardeeStateCode: IL\n",
      "fundsObligatedAmt: 850000\n",
      "id: 2202481\n",
      "piFirstName: Dong\n",
      "piLastName: Wang\n",
      "publicAccessMandate: 1\n",
      "date: 06/13/2022\n",
      "title: FairFL-MC: A Metacognitive Calibration Intervention Powered by Fair and Private Machine Learning\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: SAN JOSE\n",
      "awardeeName: San Jose State University Foundation\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 263253\n",
      "id: 2142783\n",
      "piFirstName: Yu\n",
      "piLastName: Chen\n",
      "publicAccessMandate: 1\n",
      "date: 05/26/2022\n",
      "title: Collaborative Research: Broadening Inclusive Participation in Artificial Intelligence Undergraduate Education for Social Good Using A Situated Learning Approach\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: POMONA\n",
      "awardeeName: Cal Poly Pomona Foundation, Inc.\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 72610\n",
      "id: 2142490\n",
      "piFirstName: Gabriel\n",
      "piLastName: Granco\n",
      "publicAccessMandate: 1\n",
      "date: 05/26/2022\n",
      "title: Collaborative Research: Broadening Inclusive Participation in Artificial Intelligence Undergraduate Education for Social Good Using A Situated Learning Approach\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: SAN BERNARDINO\n",
      "awardeeName: University Enterprises Corporation at CSUSB\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 97668\n",
      "id: 2142503\n",
      "piFirstName: Yunfei\n",
      "piLastName: Hou\n",
      "publicAccessMandate: 1\n",
      "date: 05/26/2022\n",
      "title: Collaborative Research: Broadening Inclusive Participation in Artificial Intelligence Undergraduate Education for Social Good Using A Situated Learning Approach\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: LONG BEACH\n",
      "awardeeName: California State University, Trustees\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 96812\n",
      "id: 2142439\n",
      "piFirstName: Frank\n",
      "piLastName: Gomez\n",
      "publicAccessMandate: 1\n",
      "date: 05/26/2022\n",
      "title: Collaborative Research: Broadening Inclusive Participation in Artificial Intelligence Undergraduate Education for Social Good Using A Situated Learning Approach\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: LONG BEACH\n",
      "awardeeName: California State University-Long Beach Foundation\n",
      "awardeeStateCode: CA\n",
      "fundsObligatedAmt: 68822\n",
      "id: 2142594\n",
      "piFirstName: Heather\n",
      "piLastName: Macias\n",
      "publicAccessMandate: 1\n",
      "date: 05/26/2022\n",
      "title: Collaborative Research: Broadening Inclusive Participation in Artificial Intelligence Undergraduate Education for Social Good Using A Situated Learning Approach\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: CHICAGO\n",
      "awardeeName: University of Chicago\n",
      "awardeeStateCode: IL\n",
      "fundsObligatedAmt: 10000\n",
      "id: 2229623\n",
      "piFirstName: Rebecca\n",
      "piLastName: Willett\n",
      "publicAccessMandate: 1\n",
      "date: 05/20/2022\n",
      "title: NSF Student Travel Grant for 2022 UChicago AI+Science Summer School (UChicago AI+Sci SS)\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: FAYETTEVILLE\n",
      "awardeeName: Fayetteville State University\n",
      "awardeeStateCode: NC\n",
      "fundsObligatedAmt: 397055\n",
      "id: 2205502\n",
      "piFirstName: Sambit\n",
      "piLastName: Bhattacharya\n",
      "publicAccessMandate: 1\n",
      "date: 05/03/2022\n",
      "title: Targeted Infusion Project: Exposing Students to the Social Relevance and Trustworthiness of Artificial Intelligence\n",
      "----\n",
      "agency: NSF\n",
      "awardeeCity: University Park\n",
      "awardeeName: Pennsylvania State Univ University Park\n",
      "awardeeStateCode: PA\n",
      "fundsObligatedAmt: 74790\n",
      "id: 2144887\n",
      "piFirstName: Christopher\n",
      "piLastName: Dancy\n",
      "publicAccessMandate: 1\n",
      "date: 04/07/2022\n",
      "title: CAREER: SocioCulturally Competent Agents to Study and Improve Human-AI interaction\n"
     ]
    }
   ],
   "source": [
    "# NSF awards API is found at: \n",
    "# https://www.research.gov/common/webapi/awardapisearch-v1.htm\n",
    "nsf_awards_json_api = 'http://api.nsf.gov/services/v1/awards.json'\n",
    "keywords = 'keyword=ai'\n",
    "\n",
    "# Make the URL request\n",
    "res = requests.get(nsf_awards_json_api + '?' + keywords)\n",
    "\n",
    "# Get the awards data\n",
    "json_response = res.json()[\"response\"]\n",
    "print(f'type(awards): {type(json_response)}')\n",
    "awards = json_response[\"award\"]\n",
    "\n",
    "# Show each award in the list of awards\n",
    "for award in awards:\n",
    "    print('----')\n",
    "    # Print the award info for each awardee\n",
    "    print(f'agency: {award[\"agency\"]}')\n",
    "    print(f'awardeeCity: {award[\"awardeeCity\"]}')\n",
    "    print(f'awardeeName: {award[\"awardeeName\"]}')\n",
    "    print(f'awardeeStateCode: {award[\"awardeeStateCode\"]}')\n",
    "    print(f'fundsObligatedAmt: {award[\"fundsObligatedAmt\"]}')\n",
    "    print(f'id: {award[\"id\"]}')\n",
    "    print(f'piFirstName: {award[\"piFirstName\"]}')\n",
    "    print(f'piLastName: {award[\"piLastName\"]}')\n",
    "    print(f'publicAccessMandate: {award[\"publicAccessMandate\"]}')\n",
    "    print(f'date: {award[\"date\"]}')\n",
    "    print(f'title: {award[\"title\"]}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "14b621c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type(awards): <class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "nsf_awards_json_api = 'http://api.nsf.gov/services/v1/awards.json'\n",
    "keywords = 'keyword=ai'\n",
    "\n",
    "# Make the URL request\n",
    "res = requests.get(nsf_awards_json_api + '?' + keywords)\n",
    "\n",
    "# Get the awards data\n",
    "json_response = res.json()[\"response\"]\n",
    "print(f'type(awards): {type(json_response)}')\n",
    "awards = json_response[\"award\"]\n",
    "\n",
    "#print(awards)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6e184f13",
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agency</th>\n",
       "      <th>awardeeCity</th>\n",
       "      <th>awardeeName</th>\n",
       "      <th>awardeeStateCode</th>\n",
       "      <th>fundsObligatedAmt</th>\n",
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       "      <th>title</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>800000</td>\n",
       "      <td>2205152</td>\n",
       "      <td>Ali</td>\n",
       "      <td>Adibi</td>\n",
       "      <td>1</td>\n",
       "      <td>09/13/2022</td>\n",
       "      <td>SCH: Intelligent Radiology Through Human-Machi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CORONA</td>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>NY</td>\n",
       "      <td>74971</td>\n",
       "      <td>2230850</td>\n",
       "      <td>Dorothy</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>1</td>\n",
       "      <td>08/31/2022</td>\n",
       "      <td>Conference on Human-Centered Approaches to Art...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>790631</td>\n",
       "      <td>2211882</td>\n",
       "      <td>Tianqi</td>\n",
       "      <td>Chen</td>\n",
       "      <td>1</td>\n",
       "      <td>08/22/2022</td>\n",
       "      <td>CNS: Medium: Ground up Adaptive Learning Syste...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOSTON</td>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>MA</td>\n",
       "      <td>299375</td>\n",
       "      <td>2147220</td>\n",
       "      <td>Ronald</td>\n",
       "      <td>Sandler</td>\n",
       "      <td>1</td>\n",
       "      <td>07/07/2022</td>\n",
       "      <td>Research Community Development Grant: Summer T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SAN BERNARDINO</td>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>CA</td>\n",
       "      <td>97668</td>\n",
       "      <td>2142503</td>\n",
       "      <td>Yunfei</td>\n",
       "      <td>Hou</td>\n",
       "      <td>1</td>\n",
       "      <td>05/26/2022</td>\n",
       "      <td>Collaborative Research: Broadening Inclusive P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NSF</td>\n",
       "      <td>FAYETTEVILLE</td>\n",
       "      <td>Fayetteville State University</td>\n",
       "      <td>NC</td>\n",
       "      <td>397055</td>\n",
       "      <td>2205502</td>\n",
       "      <td>Sambit</td>\n",
       "      <td>Bhattacharya</td>\n",
       "      <td>1</td>\n",
       "      <td>05/03/2022</td>\n",
       "      <td>Targeted Infusion Project: Exposing Students t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW BRUNSWICK</td>\n",
       "      <td>Rutgers University New Brunswick</td>\n",
       "      <td>NJ</td>\n",
       "      <td>20000</td>\n",
       "      <td>2137245</td>\n",
       "      <td>Jorge</td>\n",
       "      <td>Ortiz</td>\n",
       "      <td>1</td>\n",
       "      <td>02/16/2022</td>\n",
       "      <td>IUCRC Planning Grant Rutgers University: Cente...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Richardson</td>\n",
       "      <td>University of Texas at Dallas</td>\n",
       "      <td>TX</td>\n",
       "      <td>96488</td>\n",
       "      <td>2146448</td>\n",
       "      <td>Shuang</td>\n",
       "      <td>Hao</td>\n",
       "      <td>1</td>\n",
       "      <td>01/13/2022</td>\n",
       "      <td>CAREER: Empowering White-box Driven Analytics ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LOS ANGELES</td>\n",
       "      <td>OPAL AI INC.</td>\n",
       "      <td>CA</td>\n",
       "      <td>276000</td>\n",
       "      <td>2126752</td>\n",
       "      <td>Shahrouz</td>\n",
       "      <td>Alimo</td>\n",
       "      <td>1</td>\n",
       "      <td>01/03/2022</td>\n",
       "      <td>SBIR Phase I:  Autonomous Floorplan Reconstruc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>866000</td>\n",
       "      <td>2118924</td>\n",
       "      <td>Nikolas</td>\n",
       "      <td>Martelaro</td>\n",
       "      <td>1</td>\n",
       "      <td>08/12/2021</td>\n",
       "      <td>Supporting Designers in Learning to Co-create ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>7980446</td>\n",
       "      <td>2112633</td>\n",
       "      <td>Sonia</td>\n",
       "      <td>Chernova</td>\n",
       "      <td>1</td>\n",
       "      <td>07/28/2021</td>\n",
       "      <td>AI Institute for Collaborative Assistance and ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NSF</td>\n",
       "      <td>MIAMI</td>\n",
       "      <td>Miami Dade College</td>\n",
       "      <td>FL</td>\n",
       "      <td>986535</td>\n",
       "      <td>2115153</td>\n",
       "      <td>Antonio</td>\n",
       "      <td>Delgado</td>\n",
       "      <td>1</td>\n",
       "      <td>07/12/2021</td>\n",
       "      <td>Artificial Intelligence For All: A Framework f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CLEMSON</td>\n",
       "      <td>Clemson University</td>\n",
       "      <td>SC</td>\n",
       "      <td>146000</td>\n",
       "      <td>2114920</td>\n",
       "      <td>Long</td>\n",
       "      <td>Cheng</td>\n",
       "      <td>1</td>\n",
       "      <td>05/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Learn...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GREENSBORO</td>\n",
       "      <td>North Carolina Agricultural &amp; Technical State ...</td>\n",
       "      <td>NC</td>\n",
       "      <td>100000</td>\n",
       "      <td>2114936</td>\n",
       "      <td>Xiaohong</td>\n",
       "      <td>Yuan</td>\n",
       "      <td>1</td>\n",
       "      <td>05/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Learn...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW YORK</td>\n",
       "      <td>New York University</td>\n",
       "      <td>NY</td>\n",
       "      <td>299926</td>\n",
       "      <td>2103936</td>\n",
       "      <td>Carlos</td>\n",
       "      <td>Fernandez Granda</td>\n",
       "      <td>1</td>\n",
       "      <td>05/24/2021</td>\n",
       "      <td>Elements: Collaborative Research: Community-dr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WEST LAFAYETTE</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>IN</td>\n",
       "      <td>299934</td>\n",
       "      <td>2114974</td>\n",
       "      <td>Jin</td>\n",
       "      <td>Wei-Kocsis</td>\n",
       "      <td>1</td>\n",
       "      <td>04/27/2021</td>\n",
       "      <td>EAGER: SaTC-EDU: Cybersecurity Education in th...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Champaign</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>IL</td>\n",
       "      <td>168670</td>\n",
       "      <td>2113955</td>\n",
       "      <td>Colleen</td>\n",
       "      <td>Lewis</td>\n",
       "      <td>1</td>\n",
       "      <td>04/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Artif...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOULDER</td>\n",
       "      <td>University of Colorado at Boulder</td>\n",
       "      <td>CO</td>\n",
       "      <td>11996931</td>\n",
       "      <td>2019805</td>\n",
       "      <td>Sidney</td>\n",
       "      <td>D'Mello</td>\n",
       "      <td>1</td>\n",
       "      <td>08/25/2020</td>\n",
       "      <td>AI Institute:  Institute for Student-AI Teaming</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PHILADELPHIA</td>\n",
       "      <td>University of Pennsylvania</td>\n",
       "      <td>PA</td>\n",
       "      <td>500000</td>\n",
       "      <td>2020312</td>\n",
       "      <td>Konrad</td>\n",
       "      <td>Kording</td>\n",
       "      <td>1</td>\n",
       "      <td>08/25/2020</td>\n",
       "      <td>AI Institute: Planning: From Biological Intell...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LOS ANGELES</td>\n",
       "      <td>University of California-Los Angeles</td>\n",
       "      <td>CA</td>\n",
       "      <td>98280</td>\n",
       "      <td>2049670</td>\n",
       "      <td>James</td>\n",
       "      <td>Davis</td>\n",
       "      <td>1</td>\n",
       "      <td>08/21/2020</td>\n",
       "      <td>Workshop:  Aligning AI and U.S. Advanced Manuf...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NOTRE DAME</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>IN</td>\n",
       "      <td>0</td>\n",
       "      <td>2008228</td>\n",
       "      <td>Dong</td>\n",
       "      <td>Wang</td>\n",
       "      <td>1</td>\n",
       "      <td>08/21/2020</td>\n",
       "      <td>CHS: Small: DeepCrowd: A Crowd-assisted Deep L...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SALT LAKE CITY</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>UT</td>\n",
       "      <td>316000</td>\n",
       "      <td>2041960</td>\n",
       "      <td>Eliane</td>\n",
       "      <td>Wiese</td>\n",
       "      <td>1</td>\n",
       "      <td>07/29/2020</td>\n",
       "      <td>EAGER: SaTC-EDU: Teaching Security in Undergra...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BERKELEY</td>\n",
       "      <td>University of California-Berkeley</td>\n",
       "      <td>CA</td>\n",
       "      <td>299987</td>\n",
       "      <td>2039637</td>\n",
       "      <td>Matthew A.</td>\n",
       "      <td>Cannady</td>\n",
       "      <td>1</td>\n",
       "      <td>07/28/2020</td>\n",
       "      <td>EAGER: SaTC-EDU: A transdisciplinary program f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WASHINGTON</td>\n",
       "      <td>Digital Promise Global</td>\n",
       "      <td>DC</td>\n",
       "      <td>49952</td>\n",
       "      <td>2040753</td>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Roschelle</td>\n",
       "      <td>1</td>\n",
       "      <td>07/16/2020</td>\n",
       "      <td>AI and the Future of STEM Learning: Engaging R...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NSF</td>\n",
       "      <td>COLUMBUS</td>\n",
       "      <td>Ohio State University</td>\n",
       "      <td>OH</td>\n",
       "      <td>83529</td>\n",
       "      <td>2024736</td>\n",
       "      <td>Julie</td>\n",
       "      <td>Martin</td>\n",
       "      <td>1</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>Collaborative Research: Research Initiation: E...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   agency     awardeeCity                                        awardeeName  \\\n",
       "0     NSF         ATLANTA                  Georgia Tech Research Corporation   \n",
       "1     NSF          CORONA                           New York Hall of Science   \n",
       "2     NSF      PITTSBURGH                         Carnegie-Mellon University   \n",
       "3     NSF          BOSTON                            Northeastern University   \n",
       "4     NSF  SAN BERNARDINO        University Enterprises Corporation at CSUSB   \n",
       "5     NSF    FAYETTEVILLE                      Fayetteville State University   \n",
       "6     NSF   NEW BRUNSWICK                   Rutgers University New Brunswick   \n",
       "7     NSF      Richardson                      University of Texas at Dallas   \n",
       "8     NSF     LOS ANGELES                                       OPAL AI INC.   \n",
       "9     NSF      PITTSBURGH                         Carnegie-Mellon University   \n",
       "10    NSF         ATLANTA                  Georgia Tech Research Corporation   \n",
       "11    NSF           MIAMI                                 Miami Dade College   \n",
       "12    NSF         CLEMSON                                 Clemson University   \n",
       "13    NSF      GREENSBORO  North Carolina Agricultural & Technical State ...   \n",
       "14    NSF        NEW YORK                                New York University   \n",
       "15    NSF  WEST LAFAYETTE                                  Purdue University   \n",
       "16    NSF       Champaign         University of Illinois at Urbana-Champaign   \n",
       "17    NSF         BOULDER                  University of Colorado at Boulder   \n",
       "18    NSF    PHILADELPHIA                         University of Pennsylvania   \n",
       "19    NSF     LOS ANGELES               University of California-Los Angeles   \n",
       "20    NSF      NOTRE DAME                           University of Notre Dame   \n",
       "21    NSF  SALT LAKE CITY                                 University of Utah   \n",
       "22    NSF        BERKELEY                  University of California-Berkeley   \n",
       "23    NSF      WASHINGTON                             Digital Promise Global   \n",
       "24    NSF        COLUMBUS                              Ohio State University   \n",
       "\n",
       "   awardeeStateCode fundsObligatedAmt       id piFirstName        piLastName  \\\n",
       "0                GA            800000  2205152         Ali             Adibi   \n",
       "1                NY             74971  2230850     Dorothy           Bennett   \n",
       "2                PA            790631  2211882      Tianqi              Chen   \n",
       "3                MA            299375  2147220      Ronald           Sandler   \n",
       "4                CA             97668  2142503      Yunfei               Hou   \n",
       "5                NC            397055  2205502      Sambit      Bhattacharya   \n",
       "6                NJ             20000  2137245       Jorge             Ortiz   \n",
       "7                TX             96488  2146448      Shuang               Hao   \n",
       "8                CA            276000  2126752    Shahrouz             Alimo   \n",
       "9                PA            866000  2118924     Nikolas         Martelaro   \n",
       "10               GA           7980446  2112633       Sonia          Chernova   \n",
       "11               FL            986535  2115153     Antonio           Delgado   \n",
       "12               SC            146000  2114920        Long             Cheng   \n",
       "13               NC            100000  2114936    Xiaohong              Yuan   \n",
       "14               NY            299926  2103936      Carlos  Fernandez Granda   \n",
       "15               IN            299934  2114974         Jin        Wei-Kocsis   \n",
       "16               IL            168670  2113955     Colleen             Lewis   \n",
       "17               CO          11996931  2019805      Sidney           D'Mello   \n",
       "18               PA            500000  2020312      Konrad           Kording   \n",
       "19               CA             98280  2049670       James             Davis   \n",
       "20               IN                 0  2008228        Dong              Wang   \n",
       "21               UT            316000  2041960      Eliane             Wiese   \n",
       "22               CA            299987  2039637  Matthew A.           Cannady   \n",
       "23               DC             49952  2040753      Jeremy         Roschelle   \n",
       "24               OH             83529  2024736       Julie            Martin   \n",
       "\n",
       "   publicAccessMandate        date  \\\n",
       "0                    1  09/13/2022   \n",
       "1                    1  08/31/2022   \n",
       "2                    1  08/22/2022   \n",
       "3                    1  07/07/2022   \n",
       "4                    1  05/26/2022   \n",
       "5                    1  05/03/2022   \n",
       "6                    1  02/16/2022   \n",
       "7                    1  01/13/2022   \n",
       "8                    1  01/03/2022   \n",
       "9                    1  08/12/2021   \n",
       "10                   1  07/28/2021   \n",
       "11                   1  07/12/2021   \n",
       "12                   1  05/27/2021   \n",
       "13                   1  05/27/2021   \n",
       "14                   1  05/24/2021   \n",
       "15                   1  04/27/2021   \n",
       "16                   1  04/27/2021   \n",
       "17                   1  08/25/2020   \n",
       "18                   1  08/25/2020   \n",
       "19                   1  08/21/2020   \n",
       "20                   1  08/21/2020   \n",
       "21                   1  07/29/2020   \n",
       "22                   1  07/28/2020   \n",
       "23                   1  07/16/2020   \n",
       "24                   1  07/09/2020   \n",
       "\n",
       "                                                title  \n",
       "0   SCH: Intelligent Radiology Through Human-Machi...  \n",
       "1   Conference on Human-Centered Approaches to Art...  \n",
       "2   CNS: Medium: Ground up Adaptive Learning Syste...  \n",
       "3   Research Community Development Grant: Summer T...  \n",
       "4   Collaborative Research: Broadening Inclusive P...  \n",
       "5   Targeted Infusion Project: Exposing Students t...  \n",
       "6   IUCRC Planning Grant Rutgers University: Cente...  \n",
       "7   CAREER: Empowering White-box Driven Analytics ...  \n",
       "8   SBIR Phase I:  Autonomous Floorplan Reconstruc...  \n",
       "9   Supporting Designers in Learning to Co-create ...  \n",
       "10  AI Institute for Collaborative Assistance and ...  \n",
       "11  Artificial Intelligence For All: A Framework f...  \n",
       "12  Collaborative Research: EAGER: SaTC-EDU: Learn...  \n",
       "13  Collaborative Research: EAGER: SaTC-EDU: Learn...  \n",
       "14  Elements: Collaborative Research: Community-dr...  \n",
       "15  EAGER: SaTC-EDU: Cybersecurity Education in th...  \n",
       "16  Collaborative Research: EAGER: SaTC-EDU: Artif...  \n",
       "17    AI Institute:  Institute for Student-AI Teaming  \n",
       "18  AI Institute: Planning: From Biological Intell...  \n",
       "19  Workshop:  Aligning AI and U.S. Advanced Manuf...  \n",
       "20  CHS: Small: DeepCrowd: A Crowd-assisted Deep L...  \n",
       "21  EAGER: SaTC-EDU: Teaching Security in Undergra...  \n",
       "22  EAGER: SaTC-EDU: A transdisciplinary program f...  \n",
       "23  AI and the Future of STEM Learning: Engaging R...  \n",
       "24  Collaborative Research: Research Initiation: E...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#print(awards)\n",
    "rdf = pd.json_normalize(awards)\n",
    "rdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "61a43c6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25, 11)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e3b9d5c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agency</th>\n",
       "      <th>awardeeCity</th>\n",
       "      <th>awardeeName</th>\n",
       "      <th>awardeeStateCode</th>\n",
       "      <th>fundsObligatedAmt</th>\n",
       "      <th>id</th>\n",
       "      <th>piFirstName</th>\n",
       "      <th>piLastName</th>\n",
       "      <th>publicAccessMandate</th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
       "      <th>Date2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>800000</td>\n",
       "      <td>2205152</td>\n",
       "      <td>Ali</td>\n",
       "      <td>Adibi</td>\n",
       "      <td>1</td>\n",
       "      <td>09/13/2022</td>\n",
       "      <td>SCH: Intelligent Radiology Through Human-Machi...</td>\n",
       "      <td>2022-09-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CORONA</td>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>NY</td>\n",
       "      <td>74971</td>\n",
       "      <td>2230850</td>\n",
       "      <td>Dorothy</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>1</td>\n",
       "      <td>08/31/2022</td>\n",
       "      <td>Conference on Human-Centered Approaches to Art...</td>\n",
       "      <td>2022-08-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>790631</td>\n",
       "      <td>2211882</td>\n",
       "      <td>Tianqi</td>\n",
       "      <td>Chen</td>\n",
       "      <td>1</td>\n",
       "      <td>08/22/2022</td>\n",
       "      <td>CNS: Medium: Ground up Adaptive Learning Syste...</td>\n",
       "      <td>2022-08-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOSTON</td>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>MA</td>\n",
       "      <td>299375</td>\n",
       "      <td>2147220</td>\n",
       "      <td>Ronald</td>\n",
       "      <td>Sandler</td>\n",
       "      <td>1</td>\n",
       "      <td>07/07/2022</td>\n",
       "      <td>Research Community Development Grant: Summer T...</td>\n",
       "      <td>2022-07-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SAN BERNARDINO</td>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>CA</td>\n",
       "      <td>97668</td>\n",
       "      <td>2142503</td>\n",
       "      <td>Yunfei</td>\n",
       "      <td>Hou</td>\n",
       "      <td>1</td>\n",
       "      <td>05/26/2022</td>\n",
       "      <td>Collaborative Research: Broadening Inclusive P...</td>\n",
       "      <td>2022-05-26</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  agency     awardeeCity                                  awardeeName  \\\n",
       "0    NSF         ATLANTA            Georgia Tech Research Corporation   \n",
       "1    NSF          CORONA                     New York Hall of Science   \n",
       "2    NSF      PITTSBURGH                   Carnegie-Mellon University   \n",
       "3    NSF          BOSTON                      Northeastern University   \n",
       "4    NSF  SAN BERNARDINO  University Enterprises Corporation at CSUSB   \n",
       "\n",
       "  awardeeStateCode fundsObligatedAmt       id piFirstName piLastName  \\\n",
       "0               GA            800000  2205152         Ali      Adibi   \n",
       "1               NY             74971  2230850     Dorothy    Bennett   \n",
       "2               PA            790631  2211882      Tianqi       Chen   \n",
       "3               MA            299375  2147220      Ronald    Sandler   \n",
       "4               CA             97668  2142503      Yunfei        Hou   \n",
       "\n",
       "  publicAccessMandate        date  \\\n",
       "0                   1  09/13/2022   \n",
       "1                   1  08/31/2022   \n",
       "2                   1  08/22/2022   \n",
       "3                   1  07/07/2022   \n",
       "4                   1  05/26/2022   \n",
       "\n",
       "                                               title       Date2  \n",
       "0  SCH: Intelligent Radiology Through Human-Machi...  2022-09-13  \n",
       "1  Conference on Human-Centered Approaches to Art...  2022-08-31  \n",
       "2  CNS: Medium: Ground up Adaptive Learning Syste...  2022-08-22  \n",
       "3  Research Community Development Grant: Summer T...  2022-07-07  \n",
       "4  Collaborative Research: Broadening Inclusive P...  2022-05-26  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdf['Date2'] = rdf['date'].apply(lambda x: datetime.datetime.strptime(x, '%m/%d/%Y').strftime('%Y-%m-%d'))\n",
    "rdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cbc5a470",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agency</th>\n",
       "      <th>awardeeCity</th>\n",
       "      <th>awardeeName</th>\n",
       "      <th>awardeeStateCode</th>\n",
       "      <th>fundsObligatedAmt</th>\n",
       "      <th>id</th>\n",
       "      <th>piFirstName</th>\n",
       "      <th>piLastName</th>\n",
       "      <th>publicAccessMandate</th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
       "      <th>Date2</th>\n",
       "      <th>NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>800000</td>\n",
       "      <td>2205152</td>\n",
       "      <td>Ali</td>\n",
       "      <td>Adibi</td>\n",
       "      <td>1</td>\n",
       "      <td>09/13/2022</td>\n",
       "      <td>SCH: Intelligent Radiology Through Human-Machi...</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>Ali Adibi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CORONA</td>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>NY</td>\n",
       "      <td>74971</td>\n",
       "      <td>2230850</td>\n",
       "      <td>Dorothy</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>1</td>\n",
       "      <td>08/31/2022</td>\n",
       "      <td>Conference on Human-Centered Approaches to Art...</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>Dorothy Bennett</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>790631</td>\n",
       "      <td>2211882</td>\n",
       "      <td>Tianqi</td>\n",
       "      <td>Chen</td>\n",
       "      <td>1</td>\n",
       "      <td>08/22/2022</td>\n",
       "      <td>CNS: Medium: Ground up Adaptive Learning Syste...</td>\n",
       "      <td>2022-08-22</td>\n",
       "      <td>Tianqi Chen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOSTON</td>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>MA</td>\n",
       "      <td>299375</td>\n",
       "      <td>2147220</td>\n",
       "      <td>Ronald</td>\n",
       "      <td>Sandler</td>\n",
       "      <td>1</td>\n",
       "      <td>07/07/2022</td>\n",
       "      <td>Research Community Development Grant: Summer T...</td>\n",
       "      <td>2022-07-07</td>\n",
       "      <td>Ronald Sandler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SAN BERNARDINO</td>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>CA</td>\n",
       "      <td>97668</td>\n",
       "      <td>2142503</td>\n",
       "      <td>Yunfei</td>\n",
       "      <td>Hou</td>\n",
       "      <td>1</td>\n",
       "      <td>05/26/2022</td>\n",
       "      <td>Collaborative Research: Broadening Inclusive P...</td>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>Yunfei Hou</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  agency     awardeeCity                                  awardeeName  \\\n",
       "0    NSF         ATLANTA            Georgia Tech Research Corporation   \n",
       "1    NSF          CORONA                     New York Hall of Science   \n",
       "2    NSF      PITTSBURGH                   Carnegie-Mellon University   \n",
       "3    NSF          BOSTON                      Northeastern University   \n",
       "4    NSF  SAN BERNARDINO  University Enterprises Corporation at CSUSB   \n",
       "\n",
       "  awardeeStateCode fundsObligatedAmt       id piFirstName piLastName  \\\n",
       "0               GA            800000  2205152         Ali      Adibi   \n",
       "1               NY             74971  2230850     Dorothy    Bennett   \n",
       "2               PA            790631  2211882      Tianqi       Chen   \n",
       "3               MA            299375  2147220      Ronald    Sandler   \n",
       "4               CA             97668  2142503      Yunfei        Hou   \n",
       "\n",
       "  publicAccessMandate        date  \\\n",
       "0                   1  09/13/2022   \n",
       "1                   1  08/31/2022   \n",
       "2                   1  08/22/2022   \n",
       "3                   1  07/07/2022   \n",
       "4                   1  05/26/2022   \n",
       "\n",
       "                                               title       Date2  \\\n",
       "0  SCH: Intelligent Radiology Through Human-Machi...  2022-09-13   \n",
       "1  Conference on Human-Centered Approaches to Art...  2022-08-31   \n",
       "2  CNS: Medium: Ground up Adaptive Learning Syste...  2022-08-22   \n",
       "3  Research Community Development Grant: Summer T...  2022-07-07   \n",
       "4  Collaborative Research: Broadening Inclusive P...  2022-05-26   \n",
       "\n",
       "              NAME  \n",
       "0        Ali Adibi  \n",
       "1  Dorothy Bennett  \n",
       "2      Tianqi Chen  \n",
       "3   Ronald Sandler  \n",
       "4       Yunfei Hou  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rdf['NAME'] = rdf['piFirstName'] + \" \" + rdf['piLastName']\n",
    "rdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "09959261",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Number of dollars overtime \n",
    "#agg_funds = rdf[['fundsObligatedAmt','Date2']].groupby(['Date2']).agg('sum')\n",
    "#agg_funds\n",
    "#agg_funds= agg_funds.reset_index()\n",
    "#agg_funds.columns = [\"Date\",\"Total Funds Obligated Amount\"]\n",
    "#agg_funds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c4dc7b10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Count</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>1</td>\n",
       "      <td>83529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>1</td>\n",
       "      <td>49952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>299987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>316000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>2</td>\n",
       "      <td>98280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>2</td>\n",
       "      <td>11996931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>2</td>\n",
       "      <td>299934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-05-24</td>\n",
       "      <td>1</td>\n",
       "      <td>299926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>2</td>\n",
       "      <td>146000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>1</td>\n",
       "      <td>986535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>7980446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021-08-12</td>\n",
       "      <td>1</td>\n",
       "      <td>866000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>276000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2022-01-13</td>\n",
       "      <td>1</td>\n",
       "      <td>96488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2022-02-16</td>\n",
       "      <td>1</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2022-05-03</td>\n",
       "      <td>1</td>\n",
       "      <td>397055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>1</td>\n",
       "      <td>97668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022-07-07</td>\n",
       "      <td>1</td>\n",
       "      <td>299375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022-08-22</td>\n",
       "      <td>1</td>\n",
       "      <td>790631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>1</td>\n",
       "      <td>74971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>1</td>\n",
       "      <td>800000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date Count Total Funds Obligated Amount\n",
       "0   2020-07-09     1                        83529\n",
       "1   2020-07-16     1                        49952\n",
       "2   2020-07-28     1                       299987\n",
       "3   2020-07-29     1                       316000\n",
       "4   2020-08-21     2                        98280\n",
       "5   2020-08-25     2                     11996931\n",
       "6   2021-04-27     2                       299934\n",
       "7   2021-05-24     1                       299926\n",
       "8   2021-05-27     2                       146000\n",
       "9   2021-07-12     1                       986535\n",
       "10  2021-07-28     1                      7980446\n",
       "11  2021-08-12     1                       866000\n",
       "12  2022-01-03     1                       276000\n",
       "13  2022-01-13     1                        96488\n",
       "14  2022-02-16     1                        20000\n",
       "15  2022-05-03     1                       397055\n",
       "16  2022-05-26     1                        97668\n",
       "17  2022-07-07     1                       299375\n",
       "18  2022-08-22     1                       790631\n",
       "19  2022-08-31     1                        74971\n",
       "20  2022-09-13     1                       800000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_funds2 = rdf[['fundsObligatedAmt','Date2']].groupby(['Date2']).describe()\n",
    "agg_funds2\n",
    "agg_funds2= agg_funds2.reset_index()\n",
    "agg_funds2.columns = [\"Date\",\"Count\",\"Unique\",\"Total Funds Obligated Amount\",\"Freq\"]\n",
    "agg_funds2\n",
    "agg_funds_date = agg_funds2.drop(['Unique', 'Freq'], axis=1)\n",
    "agg_funds_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "616033a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Date                             object\n",
       "Count                            object\n",
       "Total Funds Obligated Amount    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#agg_funds['Total Funds Obligated Amount']=agg_funds['Total Funds Obligated Amount'].astype(float)\n",
    "#agg_funds.dtypes\n",
    "\n",
    "agg_funds_date['Total Funds Obligated Amount']=agg_funds_date['Total Funds Obligated Amount'].astype(float)\n",
    "agg_funds_date.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c07946ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Count</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>1</td>\n",
       "      <td>83529.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>1</td>\n",
       "      <td>49952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>299987.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>316000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>2</td>\n",
       "      <td>98280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>2</td>\n",
       "      <td>11996931.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>2</td>\n",
       "      <td>299934.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-05-24</td>\n",
       "      <td>1</td>\n",
       "      <td>299926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>2</td>\n",
       "      <td>146000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>1</td>\n",
       "      <td>986535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>7980446.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021-08-12</td>\n",
       "      <td>1</td>\n",
       "      <td>866000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>276000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2022-01-13</td>\n",
       "      <td>1</td>\n",
       "      <td>96488.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2022-02-16</td>\n",
       "      <td>1</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2022-05-03</td>\n",
       "      <td>1</td>\n",
       "      <td>397055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>1</td>\n",
       "      <td>97668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022-07-07</td>\n",
       "      <td>1</td>\n",
       "      <td>299375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022-08-22</td>\n",
       "      <td>1</td>\n",
       "      <td>790631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>1</td>\n",
       "      <td>74971.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>1</td>\n",
       "      <td>800000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date Count  Total Funds Obligated Amount\n",
       "0   2020-07-09     1                       83529.0\n",
       "1   2020-07-16     1                       49952.0\n",
       "2   2020-07-28     1                      299987.0\n",
       "3   2020-07-29     1                      316000.0\n",
       "4   2020-08-21     2                       98280.0\n",
       "5   2020-08-25     2                    11996931.0\n",
       "6   2021-04-27     2                      299934.0\n",
       "7   2021-05-24     1                      299926.0\n",
       "8   2021-05-27     2                      146000.0\n",
       "9   2021-07-12     1                      986535.0\n",
       "10  2021-07-28     1                     7980446.0\n",
       "11  2021-08-12     1                      866000.0\n",
       "12  2022-01-03     1                      276000.0\n",
       "13  2022-01-13     1                       96488.0\n",
       "14  2022-02-16     1                       20000.0\n",
       "15  2022-05-03     1                      397055.0\n",
       "16  2022-05-26     1                       97668.0\n",
       "17  2022-07-07     1                      299375.0\n",
       "18  2022-08-22     1                      790631.0\n",
       "19  2022-08-31     1                       74971.0\n",
       "20  2022-09-13     1                      800000.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#finalsorted_date = agg_funds.sort_values(by = ['Total Funds Obligated Amount'], ascending = [True])\n",
    "#finalsorted_date\n",
    "final_date = agg_funds_date.sort_values(by = ['Date'], ascending = [True])\n",
    "final_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a6aa1a9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Count</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2022-02-16</td>\n",
       "      <td>1</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>1</td>\n",
       "      <td>49952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>1</td>\n",
       "      <td>74971.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>1</td>\n",
       "      <td>83529.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2022-01-13</td>\n",
       "      <td>1</td>\n",
       "      <td>96488.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>1</td>\n",
       "      <td>97668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>2</td>\n",
       "      <td>98280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>2</td>\n",
       "      <td>146000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>276000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022-07-07</td>\n",
       "      <td>1</td>\n",
       "      <td>299375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021-05-24</td>\n",
       "      <td>1</td>\n",
       "      <td>299926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>2</td>\n",
       "      <td>299934.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>299987.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>1</td>\n",
       "      <td>316000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2022-05-03</td>\n",
       "      <td>1</td>\n",
       "      <td>397055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022-08-22</td>\n",
       "      <td>1</td>\n",
       "      <td>790631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>1</td>\n",
       "      <td>800000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021-08-12</td>\n",
       "      <td>1</td>\n",
       "      <td>866000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>1</td>\n",
       "      <td>986535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2021-07-28</td>\n",
       "      <td>1</td>\n",
       "      <td>7980446.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>2</td>\n",
       "      <td>11996931.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date Count  Total Funds Obligated Amount\n",
       "14  2022-02-16     1                       20000.0\n",
       "1   2020-07-16     1                       49952.0\n",
       "19  2022-08-31     1                       74971.0\n",
       "0   2020-07-09     1                       83529.0\n",
       "13  2022-01-13     1                       96488.0\n",
       "16  2022-05-26     1                       97668.0\n",
       "4   2020-08-21     2                       98280.0\n",
       "8   2021-05-27     2                      146000.0\n",
       "12  2022-01-03     1                      276000.0\n",
       "17  2022-07-07     1                      299375.0\n",
       "7   2021-05-24     1                      299926.0\n",
       "6   2021-04-27     2                      299934.0\n",
       "2   2020-07-28     1                      299987.0\n",
       "3   2020-07-29     1                      316000.0\n",
       "15  2022-05-03     1                      397055.0\n",
       "18  2022-08-22     1                      790631.0\n",
       "20  2022-09-13     1                      800000.0\n",
       "11  2021-08-12     1                      866000.0\n",
       "9   2021-07-12     1                      986535.0\n",
       "10  2021-07-28     1                     7980446.0\n",
       "5   2020-08-25     2                    11996931.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_date2 = agg_funds_date.sort_values(by = ['Total Funds Obligated Amount'], ascending = [True])\n",
    "final_date2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e7870e95",
   "metadata": {},
   "outputs": [],
   "source": [
    "#money_overtime = final_date.plot.line(x='Date', y='Total Funds Obligated Amount', title=\"Money Overtime\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "11c22f6a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#agg_awarde = rdf[['awardeeName','fundsObligatedAmt']].groupby(['awardeeName']).agg('sum')\n",
    "#agg_awarde\n",
    "#agg_awarde= agg_awarde.reset_index()\n",
    "#agg_awarde.columns = [\"Awardee Name\",\"Total Funds Obligated Amount\"]\n",
    "#agg_awarde"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7de997f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Awardee Name</th>\n",
       "      <th>Count</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>2</td>\n",
       "      <td>790631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Clemson University</td>\n",
       "      <td>1</td>\n",
       "      <td>146000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Digital Promise Global</td>\n",
       "      <td>1</td>\n",
       "      <td>49952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fayetteville State University</td>\n",
       "      <td>1</td>\n",
       "      <td>397055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>2</td>\n",
       "      <td>800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Miami Dade College</td>\n",
       "      <td>1</td>\n",
       "      <td>986535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>1</td>\n",
       "      <td>74971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>New York University</td>\n",
       "      <td>1</td>\n",
       "      <td>299926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>North Carolina Agricultural &amp; Technical State ...</td>\n",
       "      <td>1</td>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>1</td>\n",
       "      <td>299375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>OPAL AI INC.</td>\n",
       "      <td>1</td>\n",
       "      <td>276000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ohio State University</td>\n",
       "      <td>1</td>\n",
       "      <td>83529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Purdue University</td>\n",
       "      <td>1</td>\n",
       "      <td>299934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Rutgers University New Brunswick</td>\n",
       "      <td>1</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>1</td>\n",
       "      <td>97668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>University of California-Berkeley</td>\n",
       "      <td>1</td>\n",
       "      <td>299987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>University of California-Los Angeles</td>\n",
       "      <td>1</td>\n",
       "      <td>98280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>University of Colorado at Boulder</td>\n",
       "      <td>1</td>\n",
       "      <td>11996931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>1</td>\n",
       "      <td>168670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>University of Pennsylvania</td>\n",
       "      <td>1</td>\n",
       "      <td>500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>University of Texas at Dallas</td>\n",
       "      <td>1</td>\n",
       "      <td>96488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1</td>\n",
       "      <td>316000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Awardee Name Count  \\\n",
       "0                          Carnegie-Mellon University     2   \n",
       "1                                  Clemson University     1   \n",
       "2                              Digital Promise Global     1   \n",
       "3                       Fayetteville State University     1   \n",
       "4                   Georgia Tech Research Corporation     2   \n",
       "5                                  Miami Dade College     1   \n",
       "6                            New York Hall of Science     1   \n",
       "7                                 New York University     1   \n",
       "8   North Carolina Agricultural & Technical State ...     1   \n",
       "9                             Northeastern University     1   \n",
       "10                                       OPAL AI INC.     1   \n",
       "11                              Ohio State University     1   \n",
       "12                                  Purdue University     1   \n",
       "13                   Rutgers University New Brunswick     1   \n",
       "14        University Enterprises Corporation at CSUSB     1   \n",
       "15                  University of California-Berkeley     1   \n",
       "16               University of California-Los Angeles     1   \n",
       "17                  University of Colorado at Boulder     1   \n",
       "18         University of Illinois at Urbana-Champaign     1   \n",
       "19                           University of Notre Dame     1   \n",
       "20                         University of Pennsylvania     1   \n",
       "21                      University of Texas at Dallas     1   \n",
       "22                                 University of Utah     1   \n",
       "\n",
       "   Total Funds Obligated Amount  \n",
       "0                        790631  \n",
       "1                        146000  \n",
       "2                         49952  \n",
       "3                        397055  \n",
       "4                        800000  \n",
       "5                        986535  \n",
       "6                         74971  \n",
       "7                        299926  \n",
       "8                        100000  \n",
       "9                        299375  \n",
       "10                       276000  \n",
       "11                        83529  \n",
       "12                       299934  \n",
       "13                        20000  \n",
       "14                        97668  \n",
       "15                       299987  \n",
       "16                        98280  \n",
       "17                     11996931  \n",
       "18                       168670  \n",
       "19                            0  \n",
       "20                       500000  \n",
       "21                        96488  \n",
       "22                       316000  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_awarde_school = rdf[['awardeeName','fundsObligatedAmt']].groupby(['awardeeName']).describe()\n",
    "agg_awarde_school\n",
    "agg_awarde_school= agg_awarde_school.reset_index()\n",
    "agg_awarde_school.columns = [\"Awardee Name\",\"Count\",\"Unique\",\"Total Funds Obligated Amount\",\"Freq\"]\n",
    "agg_awarde_school\n",
    "agg_awarde_school = agg_awarde_school.drop(['Unique', 'Freq'], axis=1)\n",
    "agg_awarde_school"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "854752ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Awardee Name                     object\n",
       "Count                            object\n",
       "Total Funds Obligated Amount    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_awarde_school['Total Funds Obligated Amount']=agg_awarde_school['Total Funds Obligated Amount'].astype(str).astype(float)\n",
    "agg_awarde_school.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d759d446",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Awardee Name</th>\n",
       "      <th>Count</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Rutgers University New Brunswick</td>\n",
       "      <td>1</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Digital Promise Global</td>\n",
       "      <td>1</td>\n",
       "      <td>49952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>1</td>\n",
       "      <td>74971.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ohio State University</td>\n",
       "      <td>1</td>\n",
       "      <td>83529.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>University of Texas at Dallas</td>\n",
       "      <td>1</td>\n",
       "      <td>96488.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>1</td>\n",
       "      <td>97668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>University of California-Los Angeles</td>\n",
       "      <td>1</td>\n",
       "      <td>98280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>North Carolina Agricultural &amp; Technical State ...</td>\n",
       "      <td>1</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Clemson University</td>\n",
       "      <td>1</td>\n",
       "      <td>146000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>1</td>\n",
       "      <td>168670.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>OPAL AI INC.</td>\n",
       "      <td>1</td>\n",
       "      <td>276000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>1</td>\n",
       "      <td>299375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>New York University</td>\n",
       "      <td>1</td>\n",
       "      <td>299926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Purdue University</td>\n",
       "      <td>1</td>\n",
       "      <td>299934.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>University of California-Berkeley</td>\n",
       "      <td>1</td>\n",
       "      <td>299987.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1</td>\n",
       "      <td>316000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fayetteville State University</td>\n",
       "      <td>1</td>\n",
       "      <td>397055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>University of Pennsylvania</td>\n",
       "      <td>1</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>2</td>\n",
       "      <td>790631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>2</td>\n",
       "      <td>800000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Miami Dade College</td>\n",
       "      <td>1</td>\n",
       "      <td>986535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>University of Colorado at Boulder</td>\n",
       "      <td>1</td>\n",
       "      <td>11996931.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Awardee Name Count  \\\n",
       "19                           University of Notre Dame     1   \n",
       "13                   Rutgers University New Brunswick     1   \n",
       "2                              Digital Promise Global     1   \n",
       "6                            New York Hall of Science     1   \n",
       "11                              Ohio State University     1   \n",
       "21                      University of Texas at Dallas     1   \n",
       "14        University Enterprises Corporation at CSUSB     1   \n",
       "16               University of California-Los Angeles     1   \n",
       "8   North Carolina Agricultural & Technical State ...     1   \n",
       "1                                  Clemson University     1   \n",
       "18         University of Illinois at Urbana-Champaign     1   \n",
       "10                                       OPAL AI INC.     1   \n",
       "9                             Northeastern University     1   \n",
       "7                                 New York University     1   \n",
       "12                                  Purdue University     1   \n",
       "15                  University of California-Berkeley     1   \n",
       "22                                 University of Utah     1   \n",
       "3                       Fayetteville State University     1   \n",
       "20                         University of Pennsylvania     1   \n",
       "0                          Carnegie-Mellon University     2   \n",
       "4                   Georgia Tech Research Corporation     2   \n",
       "5                                  Miami Dade College     1   \n",
       "17                  University of Colorado at Boulder     1   \n",
       "\n",
       "    Total Funds Obligated Amount  \n",
       "19                           0.0  \n",
       "13                       20000.0  \n",
       "2                        49952.0  \n",
       "6                        74971.0  \n",
       "11                       83529.0  \n",
       "21                       96488.0  \n",
       "14                       97668.0  \n",
       "16                       98280.0  \n",
       "8                       100000.0  \n",
       "1                       146000.0  \n",
       "18                      168670.0  \n",
       "10                      276000.0  \n",
       "9                       299375.0  \n",
       "7                       299926.0  \n",
       "12                      299934.0  \n",
       "15                      299987.0  \n",
       "22                      316000.0  \n",
       "3                       397055.0  \n",
       "20                      500000.0  \n",
       "0                       790631.0  \n",
       "4                       800000.0  \n",
       "5                       986535.0  \n",
       "17                    11996931.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finalsorted_school = agg_awarde_school.sort_values(by = ['Total Funds Obligated Amount'], ascending = [True])\n",
    "finalsorted_school"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "37be7bdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "funded_schools = finalsorted_school.plot.bar(x='Awardee Name', y='Total Funds Obligated Amount', title=\"Funded Institutions\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bf3cd2b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali Adibi</td>\n",
       "      <td>800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Antonio Delgado</td>\n",
       "      <td>986535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Carlos Fernandez Granda</td>\n",
       "      <td>299926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Colleen Lewis</td>\n",
       "      <td>168670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dong Wang</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dorothy Bennett</td>\n",
       "      <td>74971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Eliane Wiese</td>\n",
       "      <td>316000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>James Davis</td>\n",
       "      <td>98280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jeremy Roschelle</td>\n",
       "      <td>49952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Jin Wei-Kocsis</td>\n",
       "      <td>299934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Jorge Ortiz</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Julie Martin</td>\n",
       "      <td>83529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Konrad Kording</td>\n",
       "      <td>500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Long Cheng</td>\n",
       "      <td>146000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Matthew A. Cannady</td>\n",
       "      <td>299987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Nikolas Martelaro</td>\n",
       "      <td>866000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Ronald Sandler</td>\n",
       "      <td>299375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sambit Bhattacharya</td>\n",
       "      <td>397055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Shahrouz Alimo</td>\n",
       "      <td>276000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Shuang Hao</td>\n",
       "      <td>96488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sidney D'Mello</td>\n",
       "      <td>11996931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sonia Chernova</td>\n",
       "      <td>7980446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Tianqi Chen</td>\n",
       "      <td>790631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Xiaohong Yuan</td>\n",
       "      <td>100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Yunfei Hou</td>\n",
       "      <td>97668</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Name Total Funds Obligated Amount\n",
       "0                 Ali Adibi                       800000\n",
       "1           Antonio Delgado                       986535\n",
       "2   Carlos Fernandez Granda                       299926\n",
       "3             Colleen Lewis                       168670\n",
       "4                 Dong Wang                            0\n",
       "5           Dorothy Bennett                        74971\n",
       "6              Eliane Wiese                       316000\n",
       "7               James Davis                        98280\n",
       "8          Jeremy Roschelle                        49952\n",
       "9            Jin Wei-Kocsis                       299934\n",
       "10              Jorge Ortiz                        20000\n",
       "11             Julie Martin                        83529\n",
       "12           Konrad Kording                       500000\n",
       "13               Long Cheng                       146000\n",
       "14       Matthew A. Cannady                       299987\n",
       "15        Nikolas Martelaro                       866000\n",
       "16           Ronald Sandler                       299375\n",
       "17      Sambit Bhattacharya                       397055\n",
       "18           Shahrouz Alimo                       276000\n",
       "19               Shuang Hao                        96488\n",
       "20           Sidney D'Mello                     11996931\n",
       "21           Sonia Chernova                      7980446\n",
       "22              Tianqi Chen                       790631\n",
       "23            Xiaohong Yuan                       100000\n",
       "24               Yunfei Hou                        97668"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Take a table listing all the researchers and total amount of dollars the researchers \n",
    "#received. Most money is at the money.\n",
    "agg_name = rdf[['NAME','fundsObligatedAmt']].groupby(['NAME']).agg('sum')\n",
    "agg_name\n",
    "agg_name= agg_name.reset_index()\n",
    "agg_name.columns = [\"Name\",\"Total Funds Obligated Amount\"]\n",
    "agg_name\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "46de8253",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name                             object\n",
       "Total Funds Obligated Amount    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_name['Total Funds Obligated Amount']=agg_name['Total Funds Obligated Amount'].astype(str).astype(float)\n",
    "agg_name.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "2a71d33a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Total Funds Obligated Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dong Wang</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Jorge Ortiz</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jeremy Roschelle</td>\n",
       "      <td>49952.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dorothy Bennett</td>\n",
       "      <td>74971.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Julie Martin</td>\n",
       "      <td>83529.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Shuang Hao</td>\n",
       "      <td>96488.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Yunfei Hou</td>\n",
       "      <td>97668.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>James Davis</td>\n",
       "      <td>98280.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Xiaohong Yuan</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Long Cheng</td>\n",
       "      <td>146000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Colleen Lewis</td>\n",
       "      <td>168670.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Shahrouz Alimo</td>\n",
       "      <td>276000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Ronald Sandler</td>\n",
       "      <td>299375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Carlos Fernandez Granda</td>\n",
       "      <td>299926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Jin Wei-Kocsis</td>\n",
       "      <td>299934.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Matthew A. Cannady</td>\n",
       "      <td>299987.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Eliane Wiese</td>\n",
       "      <td>316000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Sambit Bhattacharya</td>\n",
       "      <td>397055.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Konrad Kording</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Tianqi Chen</td>\n",
       "      <td>790631.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ali Adibi</td>\n",
       "      <td>800000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Nikolas Martelaro</td>\n",
       "      <td>866000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Antonio Delgado</td>\n",
       "      <td>986535.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sonia Chernova</td>\n",
       "      <td>7980446.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Sidney D'Mello</td>\n",
       "      <td>11996931.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Name  Total Funds Obligated Amount\n",
       "4                 Dong Wang                           0.0\n",
       "10              Jorge Ortiz                       20000.0\n",
       "8          Jeremy Roschelle                       49952.0\n",
       "5           Dorothy Bennett                       74971.0\n",
       "11             Julie Martin                       83529.0\n",
       "19               Shuang Hao                       96488.0\n",
       "24               Yunfei Hou                       97668.0\n",
       "7               James Davis                       98280.0\n",
       "23            Xiaohong Yuan                      100000.0\n",
       "13               Long Cheng                      146000.0\n",
       "3             Colleen Lewis                      168670.0\n",
       "18           Shahrouz Alimo                      276000.0\n",
       "16           Ronald Sandler                      299375.0\n",
       "2   Carlos Fernandez Granda                      299926.0\n",
       "9            Jin Wei-Kocsis                      299934.0\n",
       "14       Matthew A. Cannady                      299987.0\n",
       "6              Eliane Wiese                      316000.0\n",
       "17      Sambit Bhattacharya                      397055.0\n",
       "12           Konrad Kording                      500000.0\n",
       "22              Tianqi Chen                      790631.0\n",
       "0                 Ali Adibi                      800000.0\n",
       "15        Nikolas Martelaro                      866000.0\n",
       "1           Antonio Delgado                      986535.0\n",
       "21           Sonia Chernova                     7980446.0\n",
       "20           Sidney D'Mello                    11996931.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finalsorted_name = agg_name.sort_values(by = ['Total Funds Obligated Amount'], ascending = [True])\n",
    "finalsorted_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "52609187",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "name_funds = finalsorted_name.plot.bar(x='Name', y='Total Funds Obligated Amount', title=\"Researcher Funds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1def9b90",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Nested topics (search for ai or machine learning and then do search by deep learning, \n",
    "# statistical machine learning, transformers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "089660ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agency</th>\n",
       "      <th>awardeeCity</th>\n",
       "      <th>awardeeName</th>\n",
       "      <th>awardeeStateCode</th>\n",
       "      <th>fundsObligatedAmt</th>\n",
       "      <th>id</th>\n",
       "      <th>piFirstName</th>\n",
       "      <th>piLastName</th>\n",
       "      <th>publicAccessMandate</th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
       "      <th>Date2</th>\n",
       "      <th>NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>800000</td>\n",
       "      <td>2205152</td>\n",
       "      <td>Ali</td>\n",
       "      <td>Adibi</td>\n",
       "      <td>1</td>\n",
       "      <td>09/13/2022</td>\n",
       "      <td>SCH: Intelligent Radiology Through Human-Machi...</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>Ali Adibi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CORONA</td>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>NY</td>\n",
       "      <td>74971</td>\n",
       "      <td>2230850</td>\n",
       "      <td>Dorothy</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>1</td>\n",
       "      <td>08/31/2022</td>\n",
       "      <td>Conference on Human-Centered Approaches to Art...</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>Dorothy Bennett</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>790631</td>\n",
       "      <td>2211882</td>\n",
       "      <td>Tianqi</td>\n",
       "      <td>Chen</td>\n",
       "      <td>1</td>\n",
       "      <td>08/22/2022</td>\n",
       "      <td>CNS: Medium: Ground up Adaptive Learning Syste...</td>\n",
       "      <td>2022-08-22</td>\n",
       "      <td>Tianqi Chen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOSTON</td>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>MA</td>\n",
       "      <td>299375</td>\n",
       "      <td>2147220</td>\n",
       "      <td>Ronald</td>\n",
       "      <td>Sandler</td>\n",
       "      <td>1</td>\n",
       "      <td>07/07/2022</td>\n",
       "      <td>Research Community Development Grant: Summer T...</td>\n",
       "      <td>2022-07-07</td>\n",
       "      <td>Ronald Sandler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SAN BERNARDINO</td>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>CA</td>\n",
       "      <td>97668</td>\n",
       "      <td>2142503</td>\n",
       "      <td>Yunfei</td>\n",
       "      <td>Hou</td>\n",
       "      <td>1</td>\n",
       "      <td>05/26/2022</td>\n",
       "      <td>Collaborative Research: Broadening Inclusive P...</td>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>Yunfei Hou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NSF</td>\n",
       "      <td>FAYETTEVILLE</td>\n",
       "      <td>Fayetteville State University</td>\n",
       "      <td>NC</td>\n",
       "      <td>397055</td>\n",
       "      <td>2205502</td>\n",
       "      <td>Sambit</td>\n",
       "      <td>Bhattacharya</td>\n",
       "      <td>1</td>\n",
       "      <td>05/03/2022</td>\n",
       "      <td>Targeted Infusion Project: Exposing Students t...</td>\n",
       "      <td>2022-05-03</td>\n",
       "      <td>Sambit Bhattacharya</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW BRUNSWICK</td>\n",
       "      <td>Rutgers University New Brunswick</td>\n",
       "      <td>NJ</td>\n",
       "      <td>20000</td>\n",
       "      <td>2137245</td>\n",
       "      <td>Jorge</td>\n",
       "      <td>Ortiz</td>\n",
       "      <td>1</td>\n",
       "      <td>02/16/2022</td>\n",
       "      <td>IUCRC Planning Grant Rutgers University: Cente...</td>\n",
       "      <td>2022-02-16</td>\n",
       "      <td>Jorge Ortiz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Richardson</td>\n",
       "      <td>University of Texas at Dallas</td>\n",
       "      <td>TX</td>\n",
       "      <td>96488</td>\n",
       "      <td>2146448</td>\n",
       "      <td>Shuang</td>\n",
       "      <td>Hao</td>\n",
       "      <td>1</td>\n",
       "      <td>01/13/2022</td>\n",
       "      <td>CAREER: Empowering White-box Driven Analytics ...</td>\n",
       "      <td>2022-01-13</td>\n",
       "      <td>Shuang Hao</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LOS ANGELES</td>\n",
       "      <td>OPAL AI INC.</td>\n",
       "      <td>CA</td>\n",
       "      <td>276000</td>\n",
       "      <td>2126752</td>\n",
       "      <td>Shahrouz</td>\n",
       "      <td>Alimo</td>\n",
       "      <td>1</td>\n",
       "      <td>01/03/2022</td>\n",
       "      <td>SBIR Phase I:  Autonomous Floorplan Reconstruc...</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>Shahrouz Alimo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>866000</td>\n",
       "      <td>2118924</td>\n",
       "      <td>Nikolas</td>\n",
       "      <td>Martelaro</td>\n",
       "      <td>1</td>\n",
       "      <td>08/12/2021</td>\n",
       "      <td>Supporting Designers in Learning to Co-create ...</td>\n",
       "      <td>2021-08-12</td>\n",
       "      <td>Nikolas Martelaro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>7980446</td>\n",
       "      <td>2112633</td>\n",
       "      <td>Sonia</td>\n",
       "      <td>Chernova</td>\n",
       "      <td>1</td>\n",
       "      <td>07/28/2021</td>\n",
       "      <td>AI Institute for Collaborative Assistance and ...</td>\n",
       "      <td>2021-07-28</td>\n",
       "      <td>Sonia Chernova</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NSF</td>\n",
       "      <td>MIAMI</td>\n",
       "      <td>Miami Dade College</td>\n",
       "      <td>FL</td>\n",
       "      <td>986535</td>\n",
       "      <td>2115153</td>\n",
       "      <td>Antonio</td>\n",
       "      <td>Delgado</td>\n",
       "      <td>1</td>\n",
       "      <td>07/12/2021</td>\n",
       "      <td>Artificial Intelligence For All: A Framework f...</td>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>Antonio Delgado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CLEMSON</td>\n",
       "      <td>Clemson University</td>\n",
       "      <td>SC</td>\n",
       "      <td>146000</td>\n",
       "      <td>2114920</td>\n",
       "      <td>Long</td>\n",
       "      <td>Cheng</td>\n",
       "      <td>1</td>\n",
       "      <td>05/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Learn...</td>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>Long Cheng</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GREENSBORO</td>\n",
       "      <td>North Carolina Agricultural &amp; Technical State ...</td>\n",
       "      <td>NC</td>\n",
       "      <td>100000</td>\n",
       "      <td>2114936</td>\n",
       "      <td>Xiaohong</td>\n",
       "      <td>Yuan</td>\n",
       "      <td>1</td>\n",
       "      <td>05/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Learn...</td>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>Xiaohong Yuan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW YORK</td>\n",
       "      <td>New York University</td>\n",
       "      <td>NY</td>\n",
       "      <td>299926</td>\n",
       "      <td>2103936</td>\n",
       "      <td>Carlos</td>\n",
       "      <td>Fernandez Granda</td>\n",
       "      <td>1</td>\n",
       "      <td>05/24/2021</td>\n",
       "      <td>Elements: Collaborative Research: Community-dr...</td>\n",
       "      <td>2021-05-24</td>\n",
       "      <td>Carlos Fernandez Granda</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WEST LAFAYETTE</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>IN</td>\n",
       "      <td>299934</td>\n",
       "      <td>2114974</td>\n",
       "      <td>Jin</td>\n",
       "      <td>Wei-Kocsis</td>\n",
       "      <td>1</td>\n",
       "      <td>04/27/2021</td>\n",
       "      <td>EAGER: SaTC-EDU: Cybersecurity Education in th...</td>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>Jin Wei-Kocsis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Champaign</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>IL</td>\n",
       "      <td>168670</td>\n",
       "      <td>2113955</td>\n",
       "      <td>Colleen</td>\n",
       "      <td>Lewis</td>\n",
       "      <td>1</td>\n",
       "      <td>04/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Artif...</td>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>Colleen Lewis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOULDER</td>\n",
       "      <td>University of Colorado at Boulder</td>\n",
       "      <td>CO</td>\n",
       "      <td>11996931</td>\n",
       "      <td>2019805</td>\n",
       "      <td>Sidney</td>\n",
       "      <td>D'Mello</td>\n",
       "      <td>1</td>\n",
       "      <td>08/25/2020</td>\n",
       "      <td>AI Institute:  Institute for Student-AI Teaming</td>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>Sidney D'Mello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PHILADELPHIA</td>\n",
       "      <td>University of Pennsylvania</td>\n",
       "      <td>PA</td>\n",
       "      <td>500000</td>\n",
       "      <td>2020312</td>\n",
       "      <td>Konrad</td>\n",
       "      <td>Kording</td>\n",
       "      <td>1</td>\n",
       "      <td>08/25/2020</td>\n",
       "      <td>AI Institute: Planning: From Biological Intell...</td>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>Konrad Kording</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LOS ANGELES</td>\n",
       "      <td>University of California-Los Angeles</td>\n",
       "      <td>CA</td>\n",
       "      <td>98280</td>\n",
       "      <td>2049670</td>\n",
       "      <td>James</td>\n",
       "      <td>Davis</td>\n",
       "      <td>1</td>\n",
       "      <td>08/21/2020</td>\n",
       "      <td>Workshop:  Aligning AI and U.S. Advanced Manuf...</td>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>James Davis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NOTRE DAME</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>IN</td>\n",
       "      <td>0</td>\n",
       "      <td>2008228</td>\n",
       "      <td>Dong</td>\n",
       "      <td>Wang</td>\n",
       "      <td>1</td>\n",
       "      <td>08/21/2020</td>\n",
       "      <td>CHS: Small: DeepCrowd: A Crowd-assisted Deep L...</td>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>Dong Wang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SALT LAKE CITY</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>UT</td>\n",
       "      <td>316000</td>\n",
       "      <td>2041960</td>\n",
       "      <td>Eliane</td>\n",
       "      <td>Wiese</td>\n",
       "      <td>1</td>\n",
       "      <td>07/29/2020</td>\n",
       "      <td>EAGER: SaTC-EDU: Teaching Security in Undergra...</td>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>Eliane Wiese</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BERKELEY</td>\n",
       "      <td>University of California-Berkeley</td>\n",
       "      <td>CA</td>\n",
       "      <td>299987</td>\n",
       "      <td>2039637</td>\n",
       "      <td>Matthew A.</td>\n",
       "      <td>Cannady</td>\n",
       "      <td>1</td>\n",
       "      <td>07/28/2020</td>\n",
       "      <td>EAGER: SaTC-EDU: A transdisciplinary program f...</td>\n",
       "      <td>2020-07-28</td>\n",
       "      <td>Matthew A. Cannady</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WASHINGTON</td>\n",
       "      <td>Digital Promise Global</td>\n",
       "      <td>DC</td>\n",
       "      <td>49952</td>\n",
       "      <td>2040753</td>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Roschelle</td>\n",
       "      <td>1</td>\n",
       "      <td>07/16/2020</td>\n",
       "      <td>AI and the Future of STEM Learning: Engaging R...</td>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>Jeremy Roschelle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NSF</td>\n",
       "      <td>COLUMBUS</td>\n",
       "      <td>Ohio State University</td>\n",
       "      <td>OH</td>\n",
       "      <td>83529</td>\n",
       "      <td>2024736</td>\n",
       "      <td>Julie</td>\n",
       "      <td>Martin</td>\n",
       "      <td>1</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>Collaborative Research: Research Initiation: E...</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>Julie Martin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   agency     awardeeCity                                        awardeeName  \\\n",
       "0     NSF         ATLANTA                  Georgia Tech Research Corporation   \n",
       "1     NSF          CORONA                           New York Hall of Science   \n",
       "2     NSF      PITTSBURGH                         Carnegie-Mellon University   \n",
       "3     NSF          BOSTON                            Northeastern University   \n",
       "4     NSF  SAN BERNARDINO        University Enterprises Corporation at CSUSB   \n",
       "5     NSF    FAYETTEVILLE                      Fayetteville State University   \n",
       "6     NSF   NEW BRUNSWICK                   Rutgers University New Brunswick   \n",
       "7     NSF      Richardson                      University of Texas at Dallas   \n",
       "8     NSF     LOS ANGELES                                       OPAL AI INC.   \n",
       "9     NSF      PITTSBURGH                         Carnegie-Mellon University   \n",
       "10    NSF         ATLANTA                  Georgia Tech Research Corporation   \n",
       "11    NSF           MIAMI                                 Miami Dade College   \n",
       "12    NSF         CLEMSON                                 Clemson University   \n",
       "13    NSF      GREENSBORO  North Carolina Agricultural & Technical State ...   \n",
       "14    NSF        NEW YORK                                New York University   \n",
       "15    NSF  WEST LAFAYETTE                                  Purdue University   \n",
       "16    NSF       Champaign         University of Illinois at Urbana-Champaign   \n",
       "17    NSF         BOULDER                  University of Colorado at Boulder   \n",
       "18    NSF    PHILADELPHIA                         University of Pennsylvania   \n",
       "19    NSF     LOS ANGELES               University of California-Los Angeles   \n",
       "20    NSF      NOTRE DAME                           University of Notre Dame   \n",
       "21    NSF  SALT LAKE CITY                                 University of Utah   \n",
       "22    NSF        BERKELEY                  University of California-Berkeley   \n",
       "23    NSF      WASHINGTON                             Digital Promise Global   \n",
       "24    NSF        COLUMBUS                              Ohio State University   \n",
       "\n",
       "   awardeeStateCode fundsObligatedAmt       id piFirstName        piLastName  \\\n",
       "0                GA            800000  2205152         Ali             Adibi   \n",
       "1                NY             74971  2230850     Dorothy           Bennett   \n",
       "2                PA            790631  2211882      Tianqi              Chen   \n",
       "3                MA            299375  2147220      Ronald           Sandler   \n",
       "4                CA             97668  2142503      Yunfei               Hou   \n",
       "5                NC            397055  2205502      Sambit      Bhattacharya   \n",
       "6                NJ             20000  2137245       Jorge             Ortiz   \n",
       "7                TX             96488  2146448      Shuang               Hao   \n",
       "8                CA            276000  2126752    Shahrouz             Alimo   \n",
       "9                PA            866000  2118924     Nikolas         Martelaro   \n",
       "10               GA           7980446  2112633       Sonia          Chernova   \n",
       "11               FL            986535  2115153     Antonio           Delgado   \n",
       "12               SC            146000  2114920        Long             Cheng   \n",
       "13               NC            100000  2114936    Xiaohong              Yuan   \n",
       "14               NY            299926  2103936      Carlos  Fernandez Granda   \n",
       "15               IN            299934  2114974         Jin        Wei-Kocsis   \n",
       "16               IL            168670  2113955     Colleen             Lewis   \n",
       "17               CO          11996931  2019805      Sidney           D'Mello   \n",
       "18               PA            500000  2020312      Konrad           Kording   \n",
       "19               CA             98280  2049670       James             Davis   \n",
       "20               IN                 0  2008228        Dong              Wang   \n",
       "21               UT            316000  2041960      Eliane             Wiese   \n",
       "22               CA            299987  2039637  Matthew A.           Cannady   \n",
       "23               DC             49952  2040753      Jeremy         Roschelle   \n",
       "24               OH             83529  2024736       Julie            Martin   \n",
       "\n",
       "   publicAccessMandate        date  \\\n",
       "0                    1  09/13/2022   \n",
       "1                    1  08/31/2022   \n",
       "2                    1  08/22/2022   \n",
       "3                    1  07/07/2022   \n",
       "4                    1  05/26/2022   \n",
       "5                    1  05/03/2022   \n",
       "6                    1  02/16/2022   \n",
       "7                    1  01/13/2022   \n",
       "8                    1  01/03/2022   \n",
       "9                    1  08/12/2021   \n",
       "10                   1  07/28/2021   \n",
       "11                   1  07/12/2021   \n",
       "12                   1  05/27/2021   \n",
       "13                   1  05/27/2021   \n",
       "14                   1  05/24/2021   \n",
       "15                   1  04/27/2021   \n",
       "16                   1  04/27/2021   \n",
       "17                   1  08/25/2020   \n",
       "18                   1  08/25/2020   \n",
       "19                   1  08/21/2020   \n",
       "20                   1  08/21/2020   \n",
       "21                   1  07/29/2020   \n",
       "22                   1  07/28/2020   \n",
       "23                   1  07/16/2020   \n",
       "24                   1  07/09/2020   \n",
       "\n",
       "                                                title       Date2  \\\n",
       "0   SCH: Intelligent Radiology Through Human-Machi...  2022-09-13   \n",
       "1   Conference on Human-Centered Approaches to Art...  2022-08-31   \n",
       "2   CNS: Medium: Ground up Adaptive Learning Syste...  2022-08-22   \n",
       "3   Research Community Development Grant: Summer T...  2022-07-07   \n",
       "4   Collaborative Research: Broadening Inclusive P...  2022-05-26   \n",
       "5   Targeted Infusion Project: Exposing Students t...  2022-05-03   \n",
       "6   IUCRC Planning Grant Rutgers University: Cente...  2022-02-16   \n",
       "7   CAREER: Empowering White-box Driven Analytics ...  2022-01-13   \n",
       "8   SBIR Phase I:  Autonomous Floorplan Reconstruc...  2022-01-03   \n",
       "9   Supporting Designers in Learning to Co-create ...  2021-08-12   \n",
       "10  AI Institute for Collaborative Assistance and ...  2021-07-28   \n",
       "11  Artificial Intelligence For All: A Framework f...  2021-07-12   \n",
       "12  Collaborative Research: EAGER: SaTC-EDU: Learn...  2021-05-27   \n",
       "13  Collaborative Research: EAGER: SaTC-EDU: Learn...  2021-05-27   \n",
       "14  Elements: Collaborative Research: Community-dr...  2021-05-24   \n",
       "15  EAGER: SaTC-EDU: Cybersecurity Education in th...  2021-04-27   \n",
       "16  Collaborative Research: EAGER: SaTC-EDU: Artif...  2021-04-27   \n",
       "17    AI Institute:  Institute for Student-AI Teaming  2020-08-25   \n",
       "18  AI Institute: Planning: From Biological Intell...  2020-08-25   \n",
       "19  Workshop:  Aligning AI and U.S. Advanced Manuf...  2020-08-21   \n",
       "20  CHS: Small: DeepCrowd: A Crowd-assisted Deep L...  2020-08-21   \n",
       "21  EAGER: SaTC-EDU: Teaching Security in Undergra...  2020-07-29   \n",
       "22  EAGER: SaTC-EDU: A transdisciplinary program f...  2020-07-28   \n",
       "23  AI and the Future of STEM Learning: Engaging R...  2020-07-16   \n",
       "24  Collaborative Research: Research Initiation: E...  2020-07-09   \n",
       "\n",
       "                       NAME  \n",
       "0                 Ali Adibi  \n",
       "1           Dorothy Bennett  \n",
       "2               Tianqi Chen  \n",
       "3            Ronald Sandler  \n",
       "4                Yunfei Hou  \n",
       "5       Sambit Bhattacharya  \n",
       "6               Jorge Ortiz  \n",
       "7                Shuang Hao  \n",
       "8            Shahrouz Alimo  \n",
       "9         Nikolas Martelaro  \n",
       "10           Sonia Chernova  \n",
       "11          Antonio Delgado  \n",
       "12               Long Cheng  \n",
       "13            Xiaohong Yuan  \n",
       "14  Carlos Fernandez Granda  \n",
       "15           Jin Wei-Kocsis  \n",
       "16            Colleen Lewis  \n",
       "17           Sidney D'Mello  \n",
       "18           Konrad Kording  \n",
       "19              James Davis  \n",
       "20                Dong Wang  \n",
       "21             Eliane Wiese  \n",
       "22       Matthew A. Cannady  \n",
       "23         Jeremy Roschelle  \n",
       "24             Julie Martin  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = rdf.copy(deep=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "8fc859dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type(awards): <class 'dict'>\n"
     ]
    }
   ],
   "source": [
    "res_transformers = requests.get(nsf_awards_json_api + '?' + 'keyword=transformers')\n",
    "json_response_tran = res_transformers.json()[\"response\"]\n",
    "print(f'type(awards): {type(json_response_tran)}')\n",
    "awards_tran = json_response_tran[\"award\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "30ff0b5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agency</th>\n",
       "      <th>awardeeCity</th>\n",
       "      <th>awardeeName</th>\n",
       "      <th>awardeeStateCode</th>\n",
       "      <th>fundsObligatedAmt</th>\n",
       "      <th>id</th>\n",
       "      <th>piFirstName</th>\n",
       "      <th>piLastName</th>\n",
       "      <th>publicAccessMandate</th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>KALAMAZOO</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>MI</td>\n",
       "      <td>199105</td>\n",
       "      <td>2138408</td>\n",
       "      <td>Pablo</td>\n",
       "      <td>Gomez</td>\n",
       "      <td>1</td>\n",
       "      <td>02/22/2022</td>\n",
       "      <td>ERI: Multiphysics cosimulation approach for op...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PRINCETON</td>\n",
       "      <td>Princeton University</td>\n",
       "      <td>NJ</td>\n",
       "      <td>194635</td>\n",
       "      <td>2203399</td>\n",
       "      <td>Niraj</td>\n",
       "      <td>Jha</td>\n",
       "      <td>1</td>\n",
       "      <td>01/28/2022</td>\n",
       "      <td>CCF: SHF: Small: Transformer synthesis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>STATE COLLEGE</td>\n",
       "      <td>Solid State Ceramics, Inc.</td>\n",
       "      <td>PA</td>\n",
       "      <td>764749</td>\n",
       "      <td>1632476</td>\n",
       "      <td>Safakcan</td>\n",
       "      <td>Tuncdemir</td>\n",
       "      <td>1</td>\n",
       "      <td>09/22/2016</td>\n",
       "      <td>STTR Phase II:  Low Temperature Cofired Multil...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GAINESVILLE</td>\n",
       "      <td>University of Florida</td>\n",
       "      <td>FL</td>\n",
       "      <td>200000</td>\n",
       "      <td>1611048</td>\n",
       "      <td>Shuo</td>\n",
       "      <td>Wang</td>\n",
       "      <td>0</td>\n",
       "      <td>08/17/2016</td>\n",
       "      <td>High Frequency Transformer Winding Power Loss ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LINCOLN</td>\n",
       "      <td>University of Nebraska-Lincoln</td>\n",
       "      <td>NE</td>\n",
       "      <td>500000</td>\n",
       "      <td>1554497</td>\n",
       "      <td>Liyan</td>\n",
       "      <td>Qu</td>\n",
       "      <td>0</td>\n",
       "      <td>01/27/2016</td>\n",
       "      <td>CAREER: Adjustable-Voltage-Ratio Magnetoelectr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BROOKLYN</td>\n",
       "      <td>HIGHEST Transformers Inc.</td>\n",
       "      <td>NY</td>\n",
       "      <td>207832</td>\n",
       "      <td>1521233</td>\n",
       "      <td>Qiong</td>\n",
       "      <td>Wu</td>\n",
       "      <td>0</td>\n",
       "      <td>06/24/2015</td>\n",
       "      <td>STTR Phase I:  Research and Development of Hig...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NSF</td>\n",
       "      <td>STATE COLLEGE</td>\n",
       "      <td>Solid State Ceramics, Inc.</td>\n",
       "      <td>PA</td>\n",
       "      <td>224967</td>\n",
       "      <td>1448918</td>\n",
       "      <td>Safakcan</td>\n",
       "      <td>Tuncdemir</td>\n",
       "      <td>0</td>\n",
       "      <td>12/19/2014</td>\n",
       "      <td>STTR Phase I:  Low Temperature Cofired Multila...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BURLINGTON</td>\n",
       "      <td>Winchester Technologies, LLC</td>\n",
       "      <td>MA</td>\n",
       "      <td>150000</td>\n",
       "      <td>1315213</td>\n",
       "      <td>Nian-xiang</td>\n",
       "      <td>Sun</td>\n",
       "      <td>0</td>\n",
       "      <td>05/30/2013</td>\n",
       "      <td>SBIR Phase I:  Compact and Power Efficient Int...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BLACKSBURG</td>\n",
       "      <td>Virginia Polytechnic Institute and State Unive...</td>\n",
       "      <td>VA</td>\n",
       "      <td>270962</td>\n",
       "      <td>9810688</td>\n",
       "      <td>Anbo</td>\n",
       "      <td>Wang</td>\n",
       "      <td>0</td>\n",
       "      <td>05/05/1999</td>\n",
       "      <td>Optical Fiber Sensor-Based Techniques for On-L...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Stanford</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>CA</td>\n",
       "      <td>360000</td>\n",
       "      <td>1808489</td>\n",
       "      <td>Juan Manuel</td>\n",
       "      <td>Rivas-Davila</td>\n",
       "      <td>1</td>\n",
       "      <td>08/14/2018</td>\n",
       "      <td>High-Voltage High-Power-Density Power Electron...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NSF</td>\n",
       "      <td>MILWAUKEE</td>\n",
       "      <td>University of Wisconsin-Milwaukee</td>\n",
       "      <td>WI</td>\n",
       "      <td>452978</td>\n",
       "      <td>1650470</td>\n",
       "      <td>Adel</td>\n",
       "      <td>Nasiri</td>\n",
       "      <td>1</td>\n",
       "      <td>01/19/2017</td>\n",
       "      <td>Phase II I/UCRC University of Wisconsin-Milwau...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>Massachusetts Institute of Technology</td>\n",
       "      <td>MA</td>\n",
       "      <td>265000</td>\n",
       "      <td>1609240</td>\n",
       "      <td>David</td>\n",
       "      <td>Perreault</td>\n",
       "      <td>0</td>\n",
       "      <td>06/28/2016</td>\n",
       "      <td>Collaborative Research: Advances in High-Frequ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Austin</td>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>TX</td>\n",
       "      <td>350000</td>\n",
       "      <td>1214239</td>\n",
       "      <td>Simon</td>\n",
       "      <td>Lam</td>\n",
       "      <td>0</td>\n",
       "      <td>08/17/2012</td>\n",
       "      <td>NeTS: Small: An Efficient Reachability Analysi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Wilmington</td>\n",
       "      <td>University of North Carolina at Wilmington</td>\n",
       "      <td>NC</td>\n",
       "      <td></td>\n",
       "      <td>0527193</td>\n",
       "      <td>Bongkeun</td>\n",
       "      <td>Song</td>\n",
       "      <td>0</td>\n",
       "      <td>08/29/2005</td>\n",
       "      <td>Starter Grant: Molecular Detection of Diverse ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Lawrence</td>\n",
       "      <td>University of Kansas Center for Research Inc</td>\n",
       "      <td>KS</td>\n",
       "      <td>200000</td>\n",
       "      <td>9623753</td>\n",
       "      <td>J. Michael</td>\n",
       "      <td>Ashley</td>\n",
       "      <td>0</td>\n",
       "      <td>06/07/1996</td>\n",
       "      <td>CAREER:  Employing Flow Analyses in Practical ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GLOUCESTER POINT</td>\n",
       "      <td>College of William &amp; Mary Virginia Institute o...</td>\n",
       "      <td>VA</td>\n",
       "      <td>277783</td>\n",
       "      <td>1556554</td>\n",
       "      <td>Christopher</td>\n",
       "      <td>Hein</td>\n",
       "      <td>0</td>\n",
       "      <td>03/15/2016</td>\n",
       "      <td>Collaborative Research: Ecosystems on the Edge...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WASHINGTON</td>\n",
       "      <td>George Washington University</td>\n",
       "      <td>DC</td>\n",
       "      <td>327246</td>\n",
       "      <td>1610390</td>\n",
       "      <td>Amirhossein</td>\n",
       "      <td>Etemadi</td>\n",
       "      <td>0</td>\n",
       "      <td>07/14/2016</td>\n",
       "      <td>Catastrophic impacts of geomagnetic disturbanc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW YORK</td>\n",
       "      <td>CUNY City College</td>\n",
       "      <td>NY</td>\n",
       "      <td>553114</td>\n",
       "      <td>1556556</td>\n",
       "      <td>Maria</td>\n",
       "      <td>Tzortziou</td>\n",
       "      <td>0</td>\n",
       "      <td>03/15/2016</td>\n",
       "      <td>Collaborative Research: Ecosystems on the Edge...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Cambridge</td>\n",
       "      <td>University of Maryland Center for Environmenta...</td>\n",
       "      <td>MD</td>\n",
       "      <td>341276</td>\n",
       "      <td>1556561</td>\n",
       "      <td>Raleigh</td>\n",
       "      <td>Hood</td>\n",
       "      <td>0</td>\n",
       "      <td>03/15/2016</td>\n",
       "      <td>Collaborative Research: Ecosystems on the Edge...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>University of Washington</td>\n",
       "      <td>WA</td>\n",
       "      <td>499826</td>\n",
       "      <td>2113530</td>\n",
       "      <td>Noah</td>\n",
       "      <td>Smith</td>\n",
       "      <td>1</td>\n",
       "      <td>06/30/2021</td>\n",
       "      <td>NSF-BSF: RI: Small: Efficient Transformers via...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NSF</td>\n",
       "      <td>COLLEGE STATION</td>\n",
       "      <td>Texas A&amp;M University</td>\n",
       "      <td>TX</td>\n",
       "      <td>270000</td>\n",
       "      <td>1620058</td>\n",
       "      <td>Jean-Luc</td>\n",
       "      <td>Guermond</td>\n",
       "      <td>0</td>\n",
       "      <td>08/30/2016</td>\n",
       "      <td>Advanced numerical methods for multiphysics Ma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LA JOLLA</td>\n",
       "      <td>University of California-San Diego</td>\n",
       "      <td>CA</td>\n",
       "      <td>449999</td>\n",
       "      <td>1618477</td>\n",
       "      <td>Zhuowen</td>\n",
       "      <td>Tu</td>\n",
       "      <td>0</td>\n",
       "      <td>06/28/2016</td>\n",
       "      <td>RI: Small: Unraveling and Building Top-Down Ge...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>1219459</td>\n",
       "      <td>1546329</td>\n",
       "      <td>Yiming</td>\n",
       "      <td>Yang</td>\n",
       "      <td>0</td>\n",
       "      <td>09/14/2015</td>\n",
       "      <td>BIGDATA: F: Large-Scale Transductive Learning ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Burlington</td>\n",
       "      <td>University of Vermont &amp; State Agricultural Col...</td>\n",
       "      <td>VT</td>\n",
       "      <td>408000</td>\n",
       "      <td>1254549</td>\n",
       "      <td>Paul</td>\n",
       "      <td>Hines</td>\n",
       "      <td>0</td>\n",
       "      <td>01/03/2013</td>\n",
       "      <td>CAREER: Harnessing Smart Grid Data to Enable R...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Santa Monica</td>\n",
       "      <td>Phraxos Research and Development Inc</td>\n",
       "      <td>CA</td>\n",
       "      <td></td>\n",
       "      <td>9561627</td>\n",
       "      <td>Jesse</td>\n",
       "      <td>Castaneda</td>\n",
       "      <td>0</td>\n",
       "      <td>02/21/1996</td>\n",
       "      <td>SBIR Phase I:  MHz Strip-Line Transformer for ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   agency       awardeeCity  \\\n",
       "0     NSF         KALAMAZOO   \n",
       "1     NSF         PRINCETON   \n",
       "2     NSF     STATE COLLEGE   \n",
       "3     NSF       GAINESVILLE   \n",
       "4     NSF           LINCOLN   \n",
       "5     NSF          BROOKLYN   \n",
       "6     NSF     STATE COLLEGE   \n",
       "7     NSF        BURLINGTON   \n",
       "8     NSF        BLACKSBURG   \n",
       "9     NSF          Stanford   \n",
       "10    NSF         MILWAUKEE   \n",
       "11    NSF         Cambridge   \n",
       "12    NSF            Austin   \n",
       "13    NSF        Wilmington   \n",
       "14    NSF          Lawrence   \n",
       "15    NSF  GLOUCESTER POINT   \n",
       "16    NSF        WASHINGTON   \n",
       "17    NSF          NEW YORK   \n",
       "18    NSF         Cambridge   \n",
       "19    NSF           Seattle   \n",
       "20    NSF   COLLEGE STATION   \n",
       "21    NSF          LA JOLLA   \n",
       "22    NSF        PITTSBURGH   \n",
       "23    NSF        Burlington   \n",
       "24    NSF      Santa Monica   \n",
       "\n",
       "                                          awardeeName awardeeStateCode  \\\n",
       "0                         Western Michigan University               MI   \n",
       "1                                Princeton University               NJ   \n",
       "2                          Solid State Ceramics, Inc.               PA   \n",
       "3                               University of Florida               FL   \n",
       "4                      University of Nebraska-Lincoln               NE   \n",
       "5                           HIGHEST Transformers Inc.               NY   \n",
       "6                          Solid State Ceramics, Inc.               PA   \n",
       "7                        Winchester Technologies, LLC               MA   \n",
       "8   Virginia Polytechnic Institute and State Unive...               VA   \n",
       "9                                 Stanford University               CA   \n",
       "10                  University of Wisconsin-Milwaukee               WI   \n",
       "11              Massachusetts Institute of Technology               MA   \n",
       "12                      University of Texas at Austin               TX   \n",
       "13         University of North Carolina at Wilmington               NC   \n",
       "14       University of Kansas Center for Research Inc               KS   \n",
       "15  College of William & Mary Virginia Institute o...               VA   \n",
       "16                       George Washington University               DC   \n",
       "17                                  CUNY City College               NY   \n",
       "18  University of Maryland Center for Environmenta...               MD   \n",
       "19                           University of Washington               WA   \n",
       "20                               Texas A&M University               TX   \n",
       "21                 University of California-San Diego               CA   \n",
       "22                         Carnegie-Mellon University               PA   \n",
       "23  University of Vermont & State Agricultural Col...               VT   \n",
       "24               Phraxos Research and Development Inc               CA   \n",
       "\n",
       "   fundsObligatedAmt       id  piFirstName    piLastName publicAccessMandate  \\\n",
       "0             199105  2138408        Pablo         Gomez                   1   \n",
       "1             194635  2203399        Niraj           Jha                   1   \n",
       "2             764749  1632476     Safakcan     Tuncdemir                   1   \n",
       "3             200000  1611048         Shuo          Wang                   0   \n",
       "4             500000  1554497        Liyan            Qu                   0   \n",
       "5             207832  1521233        Qiong            Wu                   0   \n",
       "6             224967  1448918     Safakcan     Tuncdemir                   0   \n",
       "7             150000  1315213   Nian-xiang           Sun                   0   \n",
       "8             270962  9810688         Anbo          Wang                   0   \n",
       "9             360000  1808489  Juan Manuel  Rivas-Davila                   1   \n",
       "10            452978  1650470         Adel        Nasiri                   1   \n",
       "11            265000  1609240        David     Perreault                   0   \n",
       "12            350000  1214239        Simon           Lam                   0   \n",
       "13                    0527193     Bongkeun          Song                   0   \n",
       "14            200000  9623753   J. Michael        Ashley                   0   \n",
       "15            277783  1556554  Christopher          Hein                   0   \n",
       "16            327246  1610390  Amirhossein       Etemadi                   0   \n",
       "17            553114  1556556        Maria     Tzortziou                   0   \n",
       "18            341276  1556561      Raleigh          Hood                   0   \n",
       "19            499826  2113530         Noah         Smith                   1   \n",
       "20            270000  1620058     Jean-Luc      Guermond                   0   \n",
       "21            449999  1618477      Zhuowen            Tu                   0   \n",
       "22           1219459  1546329       Yiming          Yang                   0   \n",
       "23            408000  1254549         Paul         Hines                   0   \n",
       "24                    9561627        Jesse     Castaneda                   0   \n",
       "\n",
       "          date                                              title  \n",
       "0   02/22/2022  ERI: Multiphysics cosimulation approach for op...  \n",
       "1   01/28/2022             CCF: SHF: Small: Transformer synthesis  \n",
       "2   09/22/2016  STTR Phase II:  Low Temperature Cofired Multil...  \n",
       "3   08/17/2016  High Frequency Transformer Winding Power Loss ...  \n",
       "4   01/27/2016  CAREER: Adjustable-Voltage-Ratio Magnetoelectr...  \n",
       "5   06/24/2015  STTR Phase I:  Research and Development of Hig...  \n",
       "6   12/19/2014  STTR Phase I:  Low Temperature Cofired Multila...  \n",
       "7   05/30/2013  SBIR Phase I:  Compact and Power Efficient Int...  \n",
       "8   05/05/1999  Optical Fiber Sensor-Based Techniques for On-L...  \n",
       "9   08/14/2018  High-Voltage High-Power-Density Power Electron...  \n",
       "10  01/19/2017  Phase II I/UCRC University of Wisconsin-Milwau...  \n",
       "11  06/28/2016  Collaborative Research: Advances in High-Frequ...  \n",
       "12  08/17/2012  NeTS: Small: An Efficient Reachability Analysi...  \n",
       "13  08/29/2005  Starter Grant: Molecular Detection of Diverse ...  \n",
       "14  06/07/1996  CAREER:  Employing Flow Analyses in Practical ...  \n",
       "15  03/15/2016  Collaborative Research: Ecosystems on the Edge...  \n",
       "16  07/14/2016  Catastrophic impacts of geomagnetic disturbanc...  \n",
       "17  03/15/2016  Collaborative Research: Ecosystems on the Edge...  \n",
       "18  03/15/2016  Collaborative Research: Ecosystems on the Edge...  \n",
       "19  06/30/2021  NSF-BSF: RI: Small: Efficient Transformers via...  \n",
       "20  08/30/2016  Advanced numerical methods for multiphysics Ma...  \n",
       "21  06/28/2016  RI: Small: Unraveling and Building Top-Down Ge...  \n",
       "22  09/14/2015  BIGDATA: F: Large-Scale Transductive Learning ...  \n",
       "23  01/03/2013  CAREER: Harnessing Smart Grid Data to Enable R...  \n",
       "24  02/21/1996  SBIR Phase I:  MHz Strip-Line Transformer for ...  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tran = pd.json_normalize(awards_tran)\n",
    "df_tran"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "bf6ace93",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>agency</th>\n",
       "      <th>awardeeCity</th>\n",
       "      <th>awardeeName</th>\n",
       "      <th>awardeeStateCode</th>\n",
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       "      <th>id</th>\n",
       "      <th>piFirstName</th>\n",
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       "      <th>publicAccessMandate</th>\n",
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       "      <th>title</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>KALAMAZOO</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>MI</td>\n",
       "      <td>199105</td>\n",
       "      <td>2138408</td>\n",
       "      <td>Pablo</td>\n",
       "      <td>Gomez</td>\n",
       "      <td>1</td>\n",
       "      <td>02/22/2022</td>\n",
       "      <td>ERI: Multiphysics cosimulation approach for op...</td>\n",
       "      <td>2022-02-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PRINCETON</td>\n",
       "      <td>Princeton University</td>\n",
       "      <td>NJ</td>\n",
       "      <td>194635</td>\n",
       "      <td>2203399</td>\n",
       "      <td>Niraj</td>\n",
       "      <td>Jha</td>\n",
       "      <td>1</td>\n",
       "      <td>01/28/2022</td>\n",
       "      <td>CCF: SHF: Small: Transformer synthesis</td>\n",
       "      <td>2022-01-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>STATE COLLEGE</td>\n",
       "      <td>Solid State Ceramics, Inc.</td>\n",
       "      <td>PA</td>\n",
       "      <td>764749</td>\n",
       "      <td>1632476</td>\n",
       "      <td>Safakcan</td>\n",
       "      <td>Tuncdemir</td>\n",
       "      <td>1</td>\n",
       "      <td>09/22/2016</td>\n",
       "      <td>STTR Phase II:  Low Temperature Cofired Multil...</td>\n",
       "      <td>2016-09-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GAINESVILLE</td>\n",
       "      <td>University of Florida</td>\n",
       "      <td>FL</td>\n",
       "      <td>200000</td>\n",
       "      <td>1611048</td>\n",
       "      <td>Shuo</td>\n",
       "      <td>Wang</td>\n",
       "      <td>0</td>\n",
       "      <td>08/17/2016</td>\n",
       "      <td>High Frequency Transformer Winding Power Loss ...</td>\n",
       "      <td>2016-08-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LINCOLN</td>\n",
       "      <td>University of Nebraska-Lincoln</td>\n",
       "      <td>NE</td>\n",
       "      <td>500000</td>\n",
       "      <td>1554497</td>\n",
       "      <td>Liyan</td>\n",
       "      <td>Qu</td>\n",
       "      <td>0</td>\n",
       "      <td>01/27/2016</td>\n",
       "      <td>CAREER: Adjustable-Voltage-Ratio Magnetoelectr...</td>\n",
       "      <td>2016-01-27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  agency    awardeeCity                     awardeeName awardeeStateCode  \\\n",
       "0    NSF      KALAMAZOO     Western Michigan University               MI   \n",
       "1    NSF      PRINCETON            Princeton University               NJ   \n",
       "2    NSF  STATE COLLEGE      Solid State Ceramics, Inc.               PA   \n",
       "3    NSF    GAINESVILLE           University of Florida               FL   \n",
       "4    NSF        LINCOLN  University of Nebraska-Lincoln               NE   \n",
       "\n",
       "  fundsObligatedAmt       id piFirstName piLastName publicAccessMandate  \\\n",
       "0            199105  2138408       Pablo      Gomez                   1   \n",
       "1            194635  2203399       Niraj        Jha                   1   \n",
       "2            764749  1632476    Safakcan  Tuncdemir                   1   \n",
       "3            200000  1611048        Shuo       Wang                   0   \n",
       "4            500000  1554497       Liyan         Qu                   0   \n",
       "\n",
       "         date                                              title       Date2  \n",
       "0  02/22/2022  ERI: Multiphysics cosimulation approach for op...  2022-02-22  \n",
       "1  01/28/2022             CCF: SHF: Small: Transformer synthesis  2022-01-28  \n",
       "2  09/22/2016  STTR Phase II:  Low Temperature Cofired Multil...  2016-09-22  \n",
       "3  08/17/2016  High Frequency Transformer Winding Power Loss ...  2016-08-17  \n",
       "4  01/27/2016  CAREER: Adjustable-Voltage-Ratio Magnetoelectr...  2016-01-27  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tran['Date2'] = df_tran['date'].apply(lambda x: datetime.datetime.strptime(x, '%m/%d/%Y').strftime('%Y-%m-%d'))\n",
    "df_tran.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "71bbb255",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>2022-02-22</td>\n",
       "      <td>Pablo Gomez</td>\n",
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       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PRINCETON</td>\n",
       "      <td>Princeton University</td>\n",
       "      <td>NJ</td>\n",
       "      <td>194635</td>\n",
       "      <td>2203399</td>\n",
       "      <td>Niraj</td>\n",
       "      <td>Jha</td>\n",
       "      <td>1</td>\n",
       "      <td>01/28/2022</td>\n",
       "      <td>CCF: SHF: Small: Transformer synthesis</td>\n",
       "      <td>2022-01-28</td>\n",
       "      <td>Niraj Jha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>STATE COLLEGE</td>\n",
       "      <td>Solid State Ceramics, Inc.</td>\n",
       "      <td>PA</td>\n",
       "      <td>764749</td>\n",
       "      <td>1632476</td>\n",
       "      <td>Safakcan</td>\n",
       "      <td>Tuncdemir</td>\n",
       "      <td>1</td>\n",
       "      <td>09/22/2016</td>\n",
       "      <td>STTR Phase II:  Low Temperature Cofired Multil...</td>\n",
       "      <td>2016-09-22</td>\n",
       "      <td>Safakcan Tuncdemir</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GAINESVILLE</td>\n",
       "      <td>University of Florida</td>\n",
       "      <td>FL</td>\n",
       "      <td>200000</td>\n",
       "      <td>1611048</td>\n",
       "      <td>Shuo</td>\n",
       "      <td>Wang</td>\n",
       "      <td>0</td>\n",
       "      <td>08/17/2016</td>\n",
       "      <td>High Frequency Transformer Winding Power Loss ...</td>\n",
       "      <td>2016-08-17</td>\n",
       "      <td>Shuo Wang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LINCOLN</td>\n",
       "      <td>University of Nebraska-Lincoln</td>\n",
       "      <td>NE</td>\n",
       "      <td>500000</td>\n",
       "      <td>1554497</td>\n",
       "      <td>Liyan</td>\n",
       "      <td>Qu</td>\n",
       "      <td>0</td>\n",
       "      <td>01/27/2016</td>\n",
       "      <td>CAREER: Adjustable-Voltage-Ratio Magnetoelectr...</td>\n",
       "      <td>2016-01-27</td>\n",
       "      <td>Liyan Qu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  agency    awardeeCity                     awardeeName awardeeStateCode  \\\n",
       "0    NSF      KALAMAZOO     Western Michigan University               MI   \n",
       "1    NSF      PRINCETON            Princeton University               NJ   \n",
       "2    NSF  STATE COLLEGE      Solid State Ceramics, Inc.               PA   \n",
       "3    NSF    GAINESVILLE           University of Florida               FL   \n",
       "4    NSF        LINCOLN  University of Nebraska-Lincoln               NE   \n",
       "\n",
       "  fundsObligatedAmt       id piFirstName piLastName publicAccessMandate  \\\n",
       "0            199105  2138408       Pablo      Gomez                   1   \n",
       "1            194635  2203399       Niraj        Jha                   1   \n",
       "2            764749  1632476    Safakcan  Tuncdemir                   1   \n",
       "3            200000  1611048        Shuo       Wang                   0   \n",
       "4            500000  1554497       Liyan         Qu                   0   \n",
       "\n",
       "         date                                              title       Date2  \\\n",
       "0  02/22/2022  ERI: Multiphysics cosimulation approach for op...  2022-02-22   \n",
       "1  01/28/2022             CCF: SHF: Small: Transformer synthesis  2022-01-28   \n",
       "2  09/22/2016  STTR Phase II:  Low Temperature Cofired Multil...  2016-09-22   \n",
       "3  08/17/2016  High Frequency Transformer Winding Power Loss ...  2016-08-17   \n",
       "4  01/27/2016  CAREER: Adjustable-Voltage-Ratio Magnetoelectr...  2016-01-27   \n",
       "\n",
       "                 NAME  \n",
       "0         Pablo Gomez  \n",
       "1           Niraj Jha  \n",
       "2  Safakcan Tuncdemir  \n",
       "3           Shuo Wang  \n",
       "4            Liyan Qu  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tran['NAME'] = df_tran['piFirstName'] + \" \" + df_tran['piLastName']\n",
    "df_tran.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7384a840",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "agency                 object\n",
       "awardeeCity            object\n",
       "awardeeName            object\n",
       "awardeeStateCode       object\n",
       "fundsObligatedAmt      object\n",
       "id                     object\n",
       "piFirstName            object\n",
       "piLastName             object\n",
       "publicAccessMandate    object\n",
       "date                   object\n",
       "title                  object\n",
       "Date2                  object\n",
       "NAME                   object\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tran.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cc073294",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "agency                 object\n",
       "awardeeCity            object\n",
       "awardeeName            object\n",
       "awardeeStateCode       object\n",
       "fundsObligatedAmt      object\n",
       "id                     object\n",
       "piFirstName            object\n",
       "piLastName             object\n",
       "publicAccessMandate    object\n",
       "date                   object\n",
       "title                  object\n",
       "Date2                  object\n",
       "NAME                   object\n",
       "dtype: object"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "d9a71e71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th>fundsObligatedAmt</th>\n",
       "      <th>id</th>\n",
       "      <th>piFirstName</th>\n",
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       "      <th>publicAccessMandate</th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
       "      <th>Date2</th>\n",
       "      <th>NAME</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [agency, awardeeCity, awardeeName, awardeeStateCode, fundsObligatedAmt, id, piFirstName, piLastName, publicAccessMandate, date, title, Date2, NAME]\n",
       "Index: []"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "common=df.merge(df_tran, how = 'inner' ,indicator=False)\n",
    "common"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "511ed437",
   "metadata": {},
   "outputs": [],
   "source": [
    "#as shown above, 0 matches between AI and transformers, but transformers is a nested topic of AI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d8f35457",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>NAME</th>\n",
       "      <th>Organization &amp; Professor</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
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       "      <td>800000</td>\n",
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       "      <td>Ali</td>\n",
       "      <td>Adibi</td>\n",
       "      <td>1</td>\n",
       "      <td>09/13/2022</td>\n",
       "      <td>SCH: Intelligent Radiology Through Human-Machi...</td>\n",
       "      <td>2022-09-13</td>\n",
       "      <td>Ali Adibi</td>\n",
       "      <td>Georgia Tech Research Corporation Ali Adibi</td>\n",
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       "      <th>1</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CORONA</td>\n",
       "      <td>New York Hall of Science</td>\n",
       "      <td>NY</td>\n",
       "      <td>74971</td>\n",
       "      <td>2230850</td>\n",
       "      <td>Dorothy</td>\n",
       "      <td>Bennett</td>\n",
       "      <td>1</td>\n",
       "      <td>08/31/2022</td>\n",
       "      <td>Conference on Human-Centered Approaches to Art...</td>\n",
       "      <td>2022-08-31</td>\n",
       "      <td>Dorothy Bennett</td>\n",
       "      <td>New York Hall of Science Dorothy Bennett</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>790631</td>\n",
       "      <td>2211882</td>\n",
       "      <td>Tianqi</td>\n",
       "      <td>Chen</td>\n",
       "      <td>1</td>\n",
       "      <td>08/22/2022</td>\n",
       "      <td>CNS: Medium: Ground up Adaptive Learning Syste...</td>\n",
       "      <td>2022-08-22</td>\n",
       "      <td>Tianqi Chen</td>\n",
       "      <td>Carnegie-Mellon University Tianqi Chen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOSTON</td>\n",
       "      <td>Northeastern University</td>\n",
       "      <td>MA</td>\n",
       "      <td>299375</td>\n",
       "      <td>2147220</td>\n",
       "      <td>Ronald</td>\n",
       "      <td>Sandler</td>\n",
       "      <td>1</td>\n",
       "      <td>07/07/2022</td>\n",
       "      <td>Research Community Development Grant: Summer T...</td>\n",
       "      <td>2022-07-07</td>\n",
       "      <td>Ronald Sandler</td>\n",
       "      <td>Northeastern University Ronald Sandler</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SAN BERNARDINO</td>\n",
       "      <td>University Enterprises Corporation at CSUSB</td>\n",
       "      <td>CA</td>\n",
       "      <td>97668</td>\n",
       "      <td>2142503</td>\n",
       "      <td>Yunfei</td>\n",
       "      <td>Hou</td>\n",
       "      <td>1</td>\n",
       "      <td>05/26/2022</td>\n",
       "      <td>Collaborative Research: Broadening Inclusive P...</td>\n",
       "      <td>2022-05-26</td>\n",
       "      <td>Yunfei Hou</td>\n",
       "      <td>University Enterprises Corporation at CSUSB Yu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NSF</td>\n",
       "      <td>FAYETTEVILLE</td>\n",
       "      <td>Fayetteville State University</td>\n",
       "      <td>NC</td>\n",
       "      <td>397055</td>\n",
       "      <td>2205502</td>\n",
       "      <td>Sambit</td>\n",
       "      <td>Bhattacharya</td>\n",
       "      <td>1</td>\n",
       "      <td>05/03/2022</td>\n",
       "      <td>Targeted Infusion Project: Exposing Students t...</td>\n",
       "      <td>2022-05-03</td>\n",
       "      <td>Sambit Bhattacharya</td>\n",
       "      <td>Fayetteville State University Sambit Bhattacharya</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW BRUNSWICK</td>\n",
       "      <td>Rutgers University New Brunswick</td>\n",
       "      <td>NJ</td>\n",
       "      <td>20000</td>\n",
       "      <td>2137245</td>\n",
       "      <td>Jorge</td>\n",
       "      <td>Ortiz</td>\n",
       "      <td>1</td>\n",
       "      <td>02/16/2022</td>\n",
       "      <td>IUCRC Planning Grant Rutgers University: Cente...</td>\n",
       "      <td>2022-02-16</td>\n",
       "      <td>Jorge Ortiz</td>\n",
       "      <td>Rutgers University New Brunswick Jorge Ortiz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Richardson</td>\n",
       "      <td>University of Texas at Dallas</td>\n",
       "      <td>TX</td>\n",
       "      <td>96488</td>\n",
       "      <td>2146448</td>\n",
       "      <td>Shuang</td>\n",
       "      <td>Hao</td>\n",
       "      <td>1</td>\n",
       "      <td>01/13/2022</td>\n",
       "      <td>CAREER: Empowering White-box Driven Analytics ...</td>\n",
       "      <td>2022-01-13</td>\n",
       "      <td>Shuang Hao</td>\n",
       "      <td>University of Texas at Dallas Shuang Hao</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LOS ANGELES</td>\n",
       "      <td>OPAL AI INC.</td>\n",
       "      <td>CA</td>\n",
       "      <td>276000</td>\n",
       "      <td>2126752</td>\n",
       "      <td>Shahrouz</td>\n",
       "      <td>Alimo</td>\n",
       "      <td>1</td>\n",
       "      <td>01/03/2022</td>\n",
       "      <td>SBIR Phase I:  Autonomous Floorplan Reconstruc...</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>Shahrouz Alimo</td>\n",
       "      <td>OPAL AI INC. Shahrouz Alimo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PITTSBURGH</td>\n",
       "      <td>Carnegie-Mellon University</td>\n",
       "      <td>PA</td>\n",
       "      <td>866000</td>\n",
       "      <td>2118924</td>\n",
       "      <td>Nikolas</td>\n",
       "      <td>Martelaro</td>\n",
       "      <td>1</td>\n",
       "      <td>08/12/2021</td>\n",
       "      <td>Supporting Designers in Learning to Co-create ...</td>\n",
       "      <td>2021-08-12</td>\n",
       "      <td>Nikolas Martelaro</td>\n",
       "      <td>Carnegie-Mellon University Nikolas Martelaro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NSF</td>\n",
       "      <td>ATLANTA</td>\n",
       "      <td>Georgia Tech Research Corporation</td>\n",
       "      <td>GA</td>\n",
       "      <td>7980446</td>\n",
       "      <td>2112633</td>\n",
       "      <td>Sonia</td>\n",
       "      <td>Chernova</td>\n",
       "      <td>1</td>\n",
       "      <td>07/28/2021</td>\n",
       "      <td>AI Institute for Collaborative Assistance and ...</td>\n",
       "      <td>2021-07-28</td>\n",
       "      <td>Sonia Chernova</td>\n",
       "      <td>Georgia Tech Research Corporation Sonia Chernova</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NSF</td>\n",
       "      <td>MIAMI</td>\n",
       "      <td>Miami Dade College</td>\n",
       "      <td>FL</td>\n",
       "      <td>986535</td>\n",
       "      <td>2115153</td>\n",
       "      <td>Antonio</td>\n",
       "      <td>Delgado</td>\n",
       "      <td>1</td>\n",
       "      <td>07/12/2021</td>\n",
       "      <td>Artificial Intelligence For All: A Framework f...</td>\n",
       "      <td>2021-07-12</td>\n",
       "      <td>Antonio Delgado</td>\n",
       "      <td>Miami Dade College Antonio Delgado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NSF</td>\n",
       "      <td>CLEMSON</td>\n",
       "      <td>Clemson University</td>\n",
       "      <td>SC</td>\n",
       "      <td>146000</td>\n",
       "      <td>2114920</td>\n",
       "      <td>Long</td>\n",
       "      <td>Cheng</td>\n",
       "      <td>1</td>\n",
       "      <td>05/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Learn...</td>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>Long Cheng</td>\n",
       "      <td>Clemson University Long Cheng</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NSF</td>\n",
       "      <td>GREENSBORO</td>\n",
       "      <td>North Carolina Agricultural &amp; Technical State ...</td>\n",
       "      <td>NC</td>\n",
       "      <td>100000</td>\n",
       "      <td>2114936</td>\n",
       "      <td>Xiaohong</td>\n",
       "      <td>Yuan</td>\n",
       "      <td>1</td>\n",
       "      <td>05/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Learn...</td>\n",
       "      <td>2021-05-27</td>\n",
       "      <td>Xiaohong Yuan</td>\n",
       "      <td>North Carolina Agricultural &amp; Technical State ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NEW YORK</td>\n",
       "      <td>New York University</td>\n",
       "      <td>NY</td>\n",
       "      <td>299926</td>\n",
       "      <td>2103936</td>\n",
       "      <td>Carlos</td>\n",
       "      <td>Fernandez Granda</td>\n",
       "      <td>1</td>\n",
       "      <td>05/24/2021</td>\n",
       "      <td>Elements: Collaborative Research: Community-dr...</td>\n",
       "      <td>2021-05-24</td>\n",
       "      <td>Carlos Fernandez Granda</td>\n",
       "      <td>New York University Carlos Fernandez Granda</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WEST LAFAYETTE</td>\n",
       "      <td>Purdue University</td>\n",
       "      <td>IN</td>\n",
       "      <td>299934</td>\n",
       "      <td>2114974</td>\n",
       "      <td>Jin</td>\n",
       "      <td>Wei-Kocsis</td>\n",
       "      <td>1</td>\n",
       "      <td>04/27/2021</td>\n",
       "      <td>EAGER: SaTC-EDU: Cybersecurity Education in th...</td>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>Jin Wei-Kocsis</td>\n",
       "      <td>Purdue University Jin Wei-Kocsis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>NSF</td>\n",
       "      <td>Champaign</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>IL</td>\n",
       "      <td>168670</td>\n",
       "      <td>2113955</td>\n",
       "      <td>Colleen</td>\n",
       "      <td>Lewis</td>\n",
       "      <td>1</td>\n",
       "      <td>04/27/2021</td>\n",
       "      <td>Collaborative Research: EAGER: SaTC-EDU: Artif...</td>\n",
       "      <td>2021-04-27</td>\n",
       "      <td>Colleen Lewis</td>\n",
       "      <td>University of Illinois at Urbana-Champaign Col...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BOULDER</td>\n",
       "      <td>University of Colorado at Boulder</td>\n",
       "      <td>CO</td>\n",
       "      <td>11996931</td>\n",
       "      <td>2019805</td>\n",
       "      <td>Sidney</td>\n",
       "      <td>D'Mello</td>\n",
       "      <td>1</td>\n",
       "      <td>08/25/2020</td>\n",
       "      <td>AI Institute:  Institute for Student-AI Teaming</td>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>Sidney D'Mello</td>\n",
       "      <td>University of Colorado at Boulder Sidney D'Mello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>NSF</td>\n",
       "      <td>PHILADELPHIA</td>\n",
       "      <td>University of Pennsylvania</td>\n",
       "      <td>PA</td>\n",
       "      <td>500000</td>\n",
       "      <td>2020312</td>\n",
       "      <td>Konrad</td>\n",
       "      <td>Kording</td>\n",
       "      <td>1</td>\n",
       "      <td>08/25/2020</td>\n",
       "      <td>AI Institute: Planning: From Biological Intell...</td>\n",
       "      <td>2020-08-25</td>\n",
       "      <td>Konrad Kording</td>\n",
       "      <td>University of Pennsylvania Konrad Kording</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>NSF</td>\n",
       "      <td>LOS ANGELES</td>\n",
       "      <td>University of California-Los Angeles</td>\n",
       "      <td>CA</td>\n",
       "      <td>98280</td>\n",
       "      <td>2049670</td>\n",
       "      <td>James</td>\n",
       "      <td>Davis</td>\n",
       "      <td>1</td>\n",
       "      <td>08/21/2020</td>\n",
       "      <td>Workshop:  Aligning AI and U.S. Advanced Manuf...</td>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>James Davis</td>\n",
       "      <td>University of California-Los Angeles James Davis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>NSF</td>\n",
       "      <td>NOTRE DAME</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>IN</td>\n",
       "      <td>0</td>\n",
       "      <td>2008228</td>\n",
       "      <td>Dong</td>\n",
       "      <td>Wang</td>\n",
       "      <td>1</td>\n",
       "      <td>08/21/2020</td>\n",
       "      <td>CHS: Small: DeepCrowd: A Crowd-assisted Deep L...</td>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>Dong Wang</td>\n",
       "      <td>University of Notre Dame Dong Wang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>NSF</td>\n",
       "      <td>SALT LAKE CITY</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>UT</td>\n",
       "      <td>316000</td>\n",
       "      <td>2041960</td>\n",
       "      <td>Eliane</td>\n",
       "      <td>Wiese</td>\n",
       "      <td>1</td>\n",
       "      <td>07/29/2020</td>\n",
       "      <td>EAGER: SaTC-EDU: Teaching Security in Undergra...</td>\n",
       "      <td>2020-07-29</td>\n",
       "      <td>Eliane Wiese</td>\n",
       "      <td>University of Utah Eliane Wiese</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>NSF</td>\n",
       "      <td>BERKELEY</td>\n",
       "      <td>University of California-Berkeley</td>\n",
       "      <td>CA</td>\n",
       "      <td>299987</td>\n",
       "      <td>2039637</td>\n",
       "      <td>Matthew A.</td>\n",
       "      <td>Cannady</td>\n",
       "      <td>1</td>\n",
       "      <td>07/28/2020</td>\n",
       "      <td>EAGER: SaTC-EDU: A transdisciplinary program f...</td>\n",
       "      <td>2020-07-28</td>\n",
       "      <td>Matthew A. Cannady</td>\n",
       "      <td>University of California-Berkeley Matthew A. C...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NSF</td>\n",
       "      <td>WASHINGTON</td>\n",
       "      <td>Digital Promise Global</td>\n",
       "      <td>DC</td>\n",
       "      <td>49952</td>\n",
       "      <td>2040753</td>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Roschelle</td>\n",
       "      <td>1</td>\n",
       "      <td>07/16/2020</td>\n",
       "      <td>AI and the Future of STEM Learning: Engaging R...</td>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>Jeremy Roschelle</td>\n",
       "      <td>Digital Promise Global Jeremy Roschelle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NSF</td>\n",
       "      <td>COLUMBUS</td>\n",
       "      <td>Ohio State University</td>\n",
       "      <td>OH</td>\n",
       "      <td>83529</td>\n",
       "      <td>2024736</td>\n",
       "      <td>Julie</td>\n",
       "      <td>Martin</td>\n",
       "      <td>1</td>\n",
       "      <td>07/09/2020</td>\n",
       "      <td>Collaborative Research: Research Initiation: E...</td>\n",
       "      <td>2020-07-09</td>\n",
       "      <td>Julie Martin</td>\n",
       "      <td>Ohio State University Julie Martin</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   agency     awardeeCity                                        awardeeName  \\\n",
       "0     NSF         ATLANTA                  Georgia Tech Research Corporation   \n",
       "1     NSF          CORONA                           New York Hall of Science   \n",
       "2     NSF      PITTSBURGH                         Carnegie-Mellon University   \n",
       "3     NSF          BOSTON                            Northeastern University   \n",
       "4     NSF  SAN BERNARDINO        University Enterprises Corporation at CSUSB   \n",
       "5     NSF    FAYETTEVILLE                      Fayetteville State University   \n",
       "6     NSF   NEW BRUNSWICK                   Rutgers University New Brunswick   \n",
       "7     NSF      Richardson                      University of Texas at Dallas   \n",
       "8     NSF     LOS ANGELES                                       OPAL AI INC.   \n",
       "9     NSF      PITTSBURGH                         Carnegie-Mellon University   \n",
       "10    NSF         ATLANTA                  Georgia Tech Research Corporation   \n",
       "11    NSF           MIAMI                                 Miami Dade College   \n",
       "12    NSF         CLEMSON                                 Clemson University   \n",
       "13    NSF      GREENSBORO  North Carolina Agricultural & Technical State ...   \n",
       "14    NSF        NEW YORK                                New York University   \n",
       "15    NSF  WEST LAFAYETTE                                  Purdue University   \n",
       "16    NSF       Champaign         University of Illinois at Urbana-Champaign   \n",
       "17    NSF         BOULDER                  University of Colorado at Boulder   \n",
       "18    NSF    PHILADELPHIA                         University of Pennsylvania   \n",
       "19    NSF     LOS ANGELES               University of California-Los Angeles   \n",
       "20    NSF      NOTRE DAME                           University of Notre Dame   \n",
       "21    NSF  SALT LAKE CITY                                 University of Utah   \n",
       "22    NSF        BERKELEY                  University of California-Berkeley   \n",
       "23    NSF      WASHINGTON                             Digital Promise Global   \n",
       "24    NSF        COLUMBUS                              Ohio State University   \n",
       "\n",
       "   awardeeStateCode fundsObligatedAmt       id piFirstName        piLastName  \\\n",
       "0                GA            800000  2205152         Ali             Adibi   \n",
       "1                NY             74971  2230850     Dorothy           Bennett   \n",
       "2                PA            790631  2211882      Tianqi              Chen   \n",
       "3                MA            299375  2147220      Ronald           Sandler   \n",
       "4                CA             97668  2142503      Yunfei               Hou   \n",
       "5                NC            397055  2205502      Sambit      Bhattacharya   \n",
       "6                NJ             20000  2137245       Jorge             Ortiz   \n",
       "7                TX             96488  2146448      Shuang               Hao   \n",
       "8                CA            276000  2126752    Shahrouz             Alimo   \n",
       "9                PA            866000  2118924     Nikolas         Martelaro   \n",
       "10               GA           7980446  2112633       Sonia          Chernova   \n",
       "11               FL            986535  2115153     Antonio           Delgado   \n",
       "12               SC            146000  2114920        Long             Cheng   \n",
       "13               NC            100000  2114936    Xiaohong              Yuan   \n",
       "14               NY            299926  2103936      Carlos  Fernandez Granda   \n",
       "15               IN            299934  2114974         Jin        Wei-Kocsis   \n",
       "16               IL            168670  2113955     Colleen             Lewis   \n",
       "17               CO          11996931  2019805      Sidney           D'Mello   \n",
       "18               PA            500000  2020312      Konrad           Kording   \n",
       "19               CA             98280  2049670       James             Davis   \n",
       "20               IN                 0  2008228        Dong              Wang   \n",
       "21               UT            316000  2041960      Eliane             Wiese   \n",
       "22               CA            299987  2039637  Matthew A.           Cannady   \n",
       "23               DC             49952  2040753      Jeremy         Roschelle   \n",
       "24               OH             83529  2024736       Julie            Martin   \n",
       "\n",
       "   publicAccessMandate        date  \\\n",
       "0                    1  09/13/2022   \n",
       "1                    1  08/31/2022   \n",
       "2                    1  08/22/2022   \n",
       "3                    1  07/07/2022   \n",
       "4                    1  05/26/2022   \n",
       "5                    1  05/03/2022   \n",
       "6                    1  02/16/2022   \n",
       "7                    1  01/13/2022   \n",
       "8                    1  01/03/2022   \n",
       "9                    1  08/12/2021   \n",
       "10                   1  07/28/2021   \n",
       "11                   1  07/12/2021   \n",
       "12                   1  05/27/2021   \n",
       "13                   1  05/27/2021   \n",
       "14                   1  05/24/2021   \n",
       "15                   1  04/27/2021   \n",
       "16                   1  04/27/2021   \n",
       "17                   1  08/25/2020   \n",
       "18                   1  08/25/2020   \n",
       "19                   1  08/21/2020   \n",
       "20                   1  08/21/2020   \n",
       "21                   1  07/29/2020   \n",
       "22                   1  07/28/2020   \n",
       "23                   1  07/16/2020   \n",
       "24                   1  07/09/2020   \n",
       "\n",
       "                                                title       Date2  \\\n",
       "0   SCH: Intelligent Radiology Through Human-Machi...  2022-09-13   \n",
       "1   Conference on Human-Centered Approaches to Art...  2022-08-31   \n",
       "2   CNS: Medium: Ground up Adaptive Learning Syste...  2022-08-22   \n",
       "3   Research Community Development Grant: Summer T...  2022-07-07   \n",
       "4   Collaborative Research: Broadening Inclusive P...  2022-05-26   \n",
       "5   Targeted Infusion Project: Exposing Students t...  2022-05-03   \n",
       "6   IUCRC Planning Grant Rutgers University: Cente...  2022-02-16   \n",
       "7   CAREER: Empowering White-box Driven Analytics ...  2022-01-13   \n",
       "8   SBIR Phase I:  Autonomous Floorplan Reconstruc...  2022-01-03   \n",
       "9   Supporting Designers in Learning to Co-create ...  2021-08-12   \n",
       "10  AI Institute for Collaborative Assistance and ...  2021-07-28   \n",
       "11  Artificial Intelligence For All: A Framework f...  2021-07-12   \n",
       "12  Collaborative Research: EAGER: SaTC-EDU: Learn...  2021-05-27   \n",
       "13  Collaborative Research: EAGER: SaTC-EDU: Learn...  2021-05-27   \n",
       "14  Elements: Collaborative Research: Community-dr...  2021-05-24   \n",
       "15  EAGER: SaTC-EDU: Cybersecurity Education in th...  2021-04-27   \n",
       "16  Collaborative Research: EAGER: SaTC-EDU: Artif...  2021-04-27   \n",
       "17    AI Institute:  Institute for Student-AI Teaming  2020-08-25   \n",
       "18  AI Institute: Planning: From Biological Intell...  2020-08-25   \n",
       "19  Workshop:  Aligning AI and U.S. Advanced Manuf...  2020-08-21   \n",
       "20  CHS: Small: DeepCrowd: A Crowd-assisted Deep L...  2020-08-21   \n",
       "21  EAGER: SaTC-EDU: Teaching Security in Undergra...  2020-07-29   \n",
       "22  EAGER: SaTC-EDU: A transdisciplinary program f...  2020-07-28   \n",
       "23  AI and the Future of STEM Learning: Engaging R...  2020-07-16   \n",
       "24  Collaborative Research: Research Initiation: E...  2020-07-09   \n",
       "\n",
       "                       NAME                           Organization & Professor  \n",
       "0                 Ali Adibi        Georgia Tech Research Corporation Ali Adibi  \n",
       "1           Dorothy Bennett           New York Hall of Science Dorothy Bennett  \n",
       "2               Tianqi Chen             Carnegie-Mellon University Tianqi Chen  \n",
       "3            Ronald Sandler             Northeastern University Ronald Sandler  \n",
       "4                Yunfei Hou  University Enterprises Corporation at CSUSB Yu...  \n",
       "5       Sambit Bhattacharya  Fayetteville State University Sambit Bhattacharya  \n",
       "6               Jorge Ortiz       Rutgers University New Brunswick Jorge Ortiz  \n",
       "7                Shuang Hao           University of Texas at Dallas Shuang Hao  \n",
       "8            Shahrouz Alimo                        OPAL AI INC. Shahrouz Alimo  \n",
       "9         Nikolas Martelaro       Carnegie-Mellon University Nikolas Martelaro  \n",
       "10           Sonia Chernova   Georgia Tech Research Corporation Sonia Chernova  \n",
       "11          Antonio Delgado                 Miami Dade College Antonio Delgado  \n",
       "12               Long Cheng                      Clemson University Long Cheng  \n",
       "13            Xiaohong Yuan  North Carolina Agricultural & Technical State ...  \n",
       "14  Carlos Fernandez Granda        New York University Carlos Fernandez Granda  \n",
       "15           Jin Wei-Kocsis                   Purdue University Jin Wei-Kocsis  \n",
       "16            Colleen Lewis  University of Illinois at Urbana-Champaign Col...  \n",
       "17           Sidney D'Mello   University of Colorado at Boulder Sidney D'Mello  \n",
       "18           Konrad Kording          University of Pennsylvania Konrad Kording  \n",
       "19              James Davis   University of California-Los Angeles James Davis  \n",
       "20                Dong Wang                 University of Notre Dame Dong Wang  \n",
       "21             Eliane Wiese                    University of Utah Eliane Wiese  \n",
       "22       Matthew A. Cannady  University of California-Berkeley Matthew A. C...  \n",
       "23         Jeremy Roschelle            Digital Promise Global Jeremy Roschelle  \n",
       "24             Julie Martin                 Ohio State University Julie Martin  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Organization & Professor\"] = df[\"awardeeName\"] + \" \" + df[\"NAME\"]\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "448e84b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "agency                      object\n",
       "awardeeCity                 object\n",
       "awardeeName                 object\n",
       "awardeeStateCode            object\n",
       "fundsObligatedAmt           object\n",
       "id                          object\n",
       "piFirstName                 object\n",
       "piLastName                  object\n",
       "publicAccessMandate         object\n",
       "date                        object\n",
       "title                       object\n",
       "Date2                       object\n",
       "NAME                        object\n",
       "Organization & Professor    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a8a62e2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df['Organization & Professor']=df['Organization & Professor'].to_string()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "0adc5810",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0           Georgia Tech Research Corporation Ali Adibi\n",
      "1              New York Hall of Science Dorothy Bennett\n",
      "2                Carnegie-Mellon University Tianqi Chen\n",
      "3                Northeastern University Ronald Sandler\n",
      "4     University Enterprises Corporation at CSUSB Yu...\n",
      "5     Fayetteville State University Sambit Bhattacharya\n",
      "6          Rutgers University New Brunswick Jorge Ortiz\n",
      "7              University of Texas at Dallas Shuang Hao\n",
      "8                           OPAL AI INC. Shahrouz Alimo\n",
      "9          Carnegie-Mellon University Nikolas Martelaro\n",
      "10     Georgia Tech Research Corporation Sonia Chernova\n",
      "11                   Miami Dade College Antonio Delgado\n",
      "12                        Clemson University Long Cheng\n",
      "13    North Carolina Agricultural & Technical State ...\n",
      "14          New York University Carlos Fernandez Granda\n",
      "15                     Purdue University Jin Wei-Kocsis\n",
      "16    University of Illinois at Urbana-Champaign Col...\n",
      "17     University of Colorado at Boulder Sidney D'Mello\n",
      "18            University of Pennsylvania Konrad Kording\n",
      "19     University of California-Los Angeles James Davis\n",
      "20                   University of Notre Dame Dong Wang\n",
      "21                      University of Utah Eliane Wiese\n",
      "22    University of California-Berkeley Matthew A. C...\n",
      "23              Digital Promise Global Jeremy Roschelle\n",
      "24                   Ohio State University Julie Martin\n"
     ]
    }
   ],
   "source": [
    "print(df['Organization & Professor'].to_string())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ad19643d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "\n",
    "#URL https://programmablesearchengine.google.com/cse?cx=13fdfa3a33e174664\n",
    "\n",
    "# get the API KEY here: https://developers.google.com/custom-search/v1/overview\n",
    "API_KEY = \"\"\n",
    "\n",
    "# get your Search Engine ID on your CSE control panel\n",
    "SEARCH_ENGINE_ID = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "fc50b246",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/far/Desktop/Personal Project/tech_scout2/tech_scout/env/lib/python3.10/site-packages/urllib3/connectionpool.py:1045: InsecureRequestWarning: Unverified HTTPS request is being made to host 'www.googleapis.com'. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/1.26.x/advanced-usage.html#ssl-warnings\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "'NoneType' object is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[38], line 9\u001b[0m\n\u001b[1;32m      7\u001b[0m data \u001b[38;5;241m=\u001b[39m requests\u001b[38;5;241m.\u001b[39mget(url, verify\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\u001b[38;5;241m.\u001b[39mjson()\n\u001b[1;32m      8\u001b[0m search_items \u001b[38;5;241m=\u001b[39m data\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mitems\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 9\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, search_item \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28;43menumerate\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msearch_items\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m:\n\u001b[1;32m     10\u001b[0m     \u001b[38;5;28mprint\u001b[39m(search_item[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlink\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m     11\u001b[0m     link_list\u001b[38;5;241m.\u001b[39mappend(search_item[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlink\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n",
      "\u001b[0;31mTypeError\u001b[0m: 'NoneType' object is not iterable"
     ]
    }
   ],
   "source": [
    "link_list = []\n",
    "for x in df['Organization & Professor']:\n",
    "    query = x + \" Research Group\"\n",
    "    page = 1\n",
    "    start = (page - 1) * 10 + 1\n",
    "    url = f\"https://www.googleapis.com/customsearch/v1?key={API_KEY}&cx={SEARCH_ENGINE_ID}&q={query}&start={start}\"\n",
    "    data = requests.get(url, verify=False).json()\n",
    "    search_items = data.get(\"items\")\n",
    "    for i, search_item in enumerate(search_items, start=1):\n",
    "        print(search_item[\"link\"])\n",
    "        link_list.append(search_item[\"link\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fb6e1ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in df['Organization & Professor']:\n",
    "    query = x + \" Research Group\"\n",
    "    print(query)\n",
    "    print(type(query))\n",
    "    page = 1\n",
    "    start = (page - 1) * 10 + 1\n",
    "    url = f\"https://www.googleapis.com/customsearch/v1?key={API_KEY}&cx={SEARCH_ENGINE_ID}&q={query}&start={start}\"\n",
    "    data = requests.get(url, verify=False).json()\n",
    "    search_items = data.get(\"items\")\n",
    "    print(search_items)\n",
    "    # iterate over 10 results found\n",
    "    for i, search_item in enumerate(search_items, start=1):\n",
    "        print('-----------')\n",
    "        # Use the following to see other available keys\n",
    "        #print(f'{search_item}, type: {type(search_item)}')\n",
    "        #print(f'Title: {search_item[\"title\"]}')\n",
    "        print(f'Link: {search_item[\"link\"]}')\n",
    "        #listie.append({search_item[\"link\"]})\n",
    "        #print(f'Snippet: {search_item[\"snippet\"]}')\n",
    "        #print(f'Pagemap: {search_item[\"pagemap\"]}')\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6784a340",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d421fc60",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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