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01-intro-code.ipynb

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{
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"cells": [
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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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"import seaborn as sns # REMOVELINE\n",
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"sns.set_context('paper') # REMOVELINE\n",
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"sns.set_style('white') # REMOVELINE"
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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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"metadata": {
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"jupytext": {
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"cell_metadata_filter": "-all",
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"main_language": "python",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3",
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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": "3.8.5"
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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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}

02-install-code.ipynb

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{
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"cells": [
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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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"lines_to_next_cell": 2
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},
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"outputs": [],
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"source": [
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"import pandas\n",
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"pandas.__version__"
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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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"lines_to_next_cell": 2
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},
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"outputs": [],
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"source": [
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"import pandas\n",
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"pandas.__version__"
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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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"lines_to_next_cell": 2
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},
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"outputs": [],
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"source": [
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"import pandas\n",
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"pandas.__version__"
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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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"#. Install pandas on your machine (using Anaconda or pip)."
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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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"#. Install Jupyter on your machine."
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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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"lines_to_next_cell": 2
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},
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"source": [
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"#. Launch Jupyter and run the following in a cell::"
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]
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}
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],
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"metadata": {
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"jupytext": {
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"cell_metadata_filter": "-all",
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"main_language": "python",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3",
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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": "3.8.5"
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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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}

03-datastructures-code.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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"#. If you had a spreadsheet with data, which pandas data structure would you use"
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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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"lines_to_next_cell": 2
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},
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"source": [
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"#. If you had a database with data, which pandas data structure would you use"
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]
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}
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],
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"metadata": {
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"jupytext": {
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"cell_metadata_filter": "-all",
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"main_language": "python",
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"notebook_metadata_filter": "-all"
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},
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"kernelspec": {
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"display_name": "Python 3",
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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": "3.8.5"
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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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}

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