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‎.gitignore

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venv
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.vscode
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.mypy_cache

‎LICENSE

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Creative Commons Legal Code
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PROVIDED HEREUNDER, AND DISCLAIMS LIABILITY FOR DAMAGES RESULTING FROM
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4. Limitations and Disclaimers.
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c. Affirmer disclaims responsibility for clearing rights of other persons
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Further, Affirmer disclaims responsibility for obtaining any necessary
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this CC0 or use of the Work.

‎README.md

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# Capstone project for YOUR NAME HERE
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![Course Hero](images/hero.png)
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[Capstone Notebook](./capstone.ipynb)
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<!--- In the next line add the URL generated by Binder in the page --->
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/)

‎capstone.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Capstone project for YOUR NAME HERE\n",
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"\n",
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"![Course Hero](images/hero.png)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Introduction\n",
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"\n",
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"Describe what is your capstone project about."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Data Set Selection\n",
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"\n",
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"Mention the data set you selected for your capstone project, where did you find it, and why it was interesting to you"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Data Examination\n",
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"\n",
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"Let's start with the imports for the notebook.\n",
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"\n",
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"Note: Remember to add in the `requirements.txt` file all the modules you use."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Get the selected data set into a pandas Dataframe.\n",
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"\n",
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"Note: You need to add the right method to load the data."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_clipboard()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Find relevant information about the selected dataset.\n",
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"\n",
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"- How many rows and columns does it has?\n",
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"- Which characteristics does each column has?\n",
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" - Data type\n",
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" - Minimum and maximum values\n",
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" - Values distribution\n",
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" - Missing data\n",
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"- Which columns are related or are dependent on each other? \n",
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" - Which ones can be derived?\n",
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" - Which are good candidates for an hypothesis?\n",
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"\n",
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"Note: Use pandas methods as shape, head, sample, groupby, describe and any other you can think of!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Define the Hypothesis to test\n",
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"\n",
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"Decide what is your project about.\n",
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"\n",
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"What do you want to predict?\n",
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"\n",
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"`Elaborate here`"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Clean the data\n",
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"\n",
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"Create a new Data Frame just with the data you are going to use"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Run your experiment(s)\n",
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"\n",
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"Describe what your experiment is done, and execute it.\n",
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"\n",
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"Note: Be generous with your plots!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Reach a conclusion\n",
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"\n",
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"What was the result of your experiment?\n",
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"\n",
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"How can it be improved?\n",
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"\n",
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"Elaborate in one thing you learn during the capstone project."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Congratulations\n",
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"\n",
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"You have finished the bootcamp!\n",
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"\n",
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"![Congratulations](images/congratulations.jpg)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.9.13 ('venv': venv)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.13"
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},
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"vscode": {
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"interpreter": {
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"hash": "21d0643b60dc6cdc4af46308b1addbbe70da23ac3fc0a0fd25c8272e747fb56f"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎images/congratulations.jpg

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‎images/hero.png

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‎images/pandas.png

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‎requirements.txt

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# Jupyter and Pandas Libraries
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jupyter
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numpy
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pandas
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matplotlib
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# Development tools
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black
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pylint
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mypy

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