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Lesson05/.ipynb_checkpoints/Activity05-checkpoint.ipynb

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Lesson05/.ipynb_checkpoints/Exercise41-checkpoint.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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"First we need to run some code from Exercise-3 for preprocessing 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": 1,
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [

Lesson05/Activity05.ipynb

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Lesson05/Exercise41.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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"First we need to run some code from Exercise-3 for preprocessing 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": 1,
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"execution_count": 5,
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"metadata": {},
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"outputs": [],
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"source": [

Lesson07/.ipynb_checkpoints/Exercise52-checkpoint.ipynb

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Lesson07/.ipynb_checkpoints/Exercise53-checkpoint.ipynb

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Lesson07/.ipynb_checkpoints/Exercise54-checkpoint.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": 1,
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"metadata": {},
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'chart_studio'",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-1-7db8bd9622ce>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mchart_studio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplotly\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpy\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 4\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgraph_objs\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mgo\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'chart_studio'"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"import numpy as np\n",
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"import chart_studio.plotly as py\n",
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"import plotly.graph_objs as go"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"co2 = pd.read_csv('../datasets/co2.csv')\n",
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"gm = pd.read_csv('../datasets/gapminder.csv')\n",
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"df_gm = gm[['Country', 'region']].drop_duplicates()\n",
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"df_w_regions = pd.merge(co2, df_gm, left_on='country', right_on='Country', how='inner')\n",
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"df_w_regions = df_w_regions.drop('Country', axis='columns')\n",
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"new_co2 = pd.melt(df_w_regions, id_vars=['country', 'region'])\n",
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"columns = ['country', 'region', 'year', 'co2']\n",
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"new_co2.columns = columns\n",
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"df_co2 = new_co2[new_co2['year'].astype('int64') > 1963]\n",
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"df_co2 = df_co2.sort_values(by=['country', 'year'])\n",
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"df_co2['year'] = df_co2['year'].astype('int64')\n",
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"df_g = gm[['Country', 'Year', 'gdp', 'population', 'fertility', 'life']]\n",
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"df_g.columns = ['country', 'year', 'gdp', 'population', 'fertility', 'life']\n",
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"data = pd.merge(df_co2, df_g, on=['country', 'year'], how='left')\n",
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"data = data.dropna()"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'go' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
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"\u001b[1;32m<ipython-input-4-a0b408726242>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 1\u001b[0m source = [\n\u001b[1;32m----> 2\u001b[1;33m go.Bar(x = data['region'], \n\u001b[0m\u001b[0;32m 3\u001b[0m y = data.co2[data['year'] == 1970]), \n\u001b[0;32m 4\u001b[0m go.Bar(x = data['region'], \n\u001b[0;32m 5\u001b[0m y = data.co2[data['year'] == 1980]), \n",
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"\u001b[1;31mNameError\u001b[0m: name 'go' is not defined"
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]
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}
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],
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"source": [
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"source = [\n",
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" go.Bar(x = data['region'], \n",
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" y = data.co2[data['year'] == 1970]), \n",
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" go.Bar(x = data['region'], \n",
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" y = data.co2[data['year'] == 1980]), \n",
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" go.Bar(x = data['region'], \n",
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" y = data.co2[data['year'] == 1990]),\n",
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" go.Bar(x = data['region'], \n",
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" y = data.co2[data['year'] == 2000]),\n",
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" go.Bar(x = data['region'], \n",
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" y = data.co2[data['year'] == 2010]),\n",
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"]\n",
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"\n",
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"layout = go.Layout(barmode = 'stack')\n",
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"\n",
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"fig = go.Figure(source, layout)\n",
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"\n",
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"fig.show()"
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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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"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": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

Lesson07/Exercise52.ipynb

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