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updates for 2020 phase 2
1 parent 31f7adf commit 046bae0

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Diff for: ‎03-Methods and Functions/.ipynb_checkpoints/02-Functions-checkpoint.ipynb

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Diff for: ‎03-Methods and Functions/02-Functions.ipynb

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Diff for: ‎08-Milestone Project - 2/00-Milestone-2-Warmup-Project.ipynb

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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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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": "3.7.4"
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"version": "3.6.6"
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}
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},
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"nbformat": 4,

Diff for: ‎15-PDFs-and-Spreadsheets/.ipynb_checkpoints/02-PDFs-Spreadsheets-Puzzle-checkpoint.ipynb

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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
@@ -45,7 +47,7 @@
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}
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],
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"source": [
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"# THe correct result is shown below, if you can't download ffrom Google Drive, \n",
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"# THe correct result is shown below, if you can't download from Google Drive, \n",
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"# we added the PDF file to the Exercise_Files folder already"
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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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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# You should get this phone number\n",
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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": "3.7.4"
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"version": "3.6.6"
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}
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},
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"nbformat": 4,

Diff for: ‎15-PDFs-and-Spreadsheets/.ipynb_checkpoints/03-PDFs-Spreadsheets-Puzzle-Solution-checkpoint.ipynb

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@@ -19,6 +19,17 @@
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"## Task One: Grab the Google Drive Link from .csv File"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import csv"
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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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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"data = open('Exercise_Files/find_the_link.csv',encoding=\"utf-8\")\n",
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"link_list = []\n",
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"link_str = ''\n",
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import PyPDF2"
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"f = open('Exercise_Files/Find_the_Phone_Number.pdf','rb')"
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"pdf = PyPDF2.PdfFileReader(f)"
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"source": [
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"## Phone Number Matching\n",
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"\n",
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"Lot's of ways to do this, but you had to figure out the phone number was in format ###.###.####"
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"Lot's of ways to do this, but you had to figure out the phone number was in format ###.###.####\n",
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"\n",
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"Hint: https://stackoverflow.com/questions/4697882/how-can-i-find-all-matches-to-a-regular-expression-in-python"
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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": 23,
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import re"
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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": 2,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"pattern = r'\\d{3}'"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"all_text = ''\n",
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"\n",
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"for n in range(pdf.numPages):\n",
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" \n",
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" page = pdf.getPage(n)\n",
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" page_text = page.extractText()\n",
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" \n",
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" all_text = all_text+' '+page_text"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"for match in re.finditer(pattern,all_text):\n",
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" print(match)"
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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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"Once you know the correct pattern:"
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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": 23,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import re"
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"pattern = r'\\d{3}.\\d{3}.\\d{4}' "
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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": "3.7.4"
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"version": "3.6.6"
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}
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},
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"nbformat": 4,

Diff for: ‎15-PDFs-and-Spreadsheets/00-Working-with-CSV-Files.ipynb

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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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},
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"outputs": [],
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"source": [
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"import csv"
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"data = open('example.csv')"
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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},
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"outputs": [],
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"source": [
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"csv_data = csv.reader(data)"
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"data = open('example.csv',encoding=\"utf-8\")\n",
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"all_emails = []\n",
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"full_names = []\n",
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"metadata": {
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},
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"outputs": [],
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"source": [
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"# newline controls how universal newlines works (it only applies to text\n",
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{
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"execution_count": 16,
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"metadata": {},
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"metadata": {
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},
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"outputs": [],
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"source": [
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"csv_writer = csv.writer(file_to_output,delimiter=',')"
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{
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},
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"outputs": [],
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"csv_writer.writerows([['1','2','3'],['4','5','6']])"
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{
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"file_to_output.close()"
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{
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},
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"outputs": [],
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"source": [
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"f = open('to_save_file.csv','a',newline='')"
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{
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"metadata": {},
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"outputs": [],
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"csv_writer = csv.writer(f)"
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{
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"execution_count": 23,
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},
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"outputs": [],
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"f.close()"
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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": "3.7.4"
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"version": "3.6.6"
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}
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},
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"nbformat": 4,

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