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Tweak section 3 for css changes
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‎notebooks/3-data_visualization.ipynb

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"source": [
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"### Line plots\n",
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"\n",
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"The `plot()` method will generate line plots for all numeric columns by default:"
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"Let's continue with the example of rolling and expanding calculations:"
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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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"id": "2e6fc032-939f-4e3a-8cb7-ee57718f0c46",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>travelers</th>\n",
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" <th>holiday</th>\n",
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" <th>7D MA</th>\n",
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" <th>YTD mean</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>date</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>2020-01-01</th>\n",
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" <td>2311732.0</td>\n",
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" <td>New Year's Day</td>\n",
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" <td>2311732.0</td>\n",
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" <td>2311732.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2020-01-02</th>\n",
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" <td>2178656.0</td>\n",
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" <td>New Year's Day</td>\n",
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" <td>2245194.0</td>\n",
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" <td>2245194.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2020-01-03</th>\n",
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" <td>2422272.0</td>\n",
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" <td>NaN</td>\n",
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" <td>2304220.0</td>\n",
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" <td>2304220.0</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2020-01-04</th>\n",
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" <td>2210542.0</td>\n",
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" <td>NaN</td>\n",
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" <td>2280800.5</td>\n",
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" <td>2280800.5</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2020-01-05</th>\n",
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" <td>1806480.0</td>\n",
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" <td>NaN</td>\n",
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" <td>2185936.4</td>\n",
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" <td>2185936.4</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" travelers holiday 7D MA YTD mean\n",
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"date \n",
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"2020-01-01 2311732.0 New Year's Day 2311732.0 2311732.0\n",
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"2020-01-02 2178656.0 New Year's Day 2245194.0 2245194.0\n",
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"2020-01-03 2422272.0 NaN 2304220.0 2304220.0\n",
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"2020-01-04 2210542.0 NaN 2280800.5 2280800.5\n",
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"2020-01-05 1806480.0 NaN 2185936.4 2185936.4"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"plot_data = tsa_melted_holiday_travel.drop(columns='year').loc['2020'].assign(\n",
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" **{\n",
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" '7D MA': lambda x: x.travelers.rolling('7D').mean(),\n",
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" 'YTD mean': lambda x: x.travelers.expanding().mean()\n",
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" }\n",
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")\n",
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"plot_data.head()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "616bc44c-4c63-4d9a-9558-8f4de0b5b3e0",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "subslide"
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},
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"tags": []
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},
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"source": [
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"The `plot()` method will generate line plots for all numeric columns by default:"
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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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"id": "7d30f224-a4c3-4083-981e-a3340f4a26b0",
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"metadata": {},
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<Axes: title={'center': '2020 TSA Traveler Throughput'}, xlabel='date', ylabel='travelers'>"
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]
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},
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"execution_count": 3,
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"execution_count": 4,
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"metadata": {},
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},
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}
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],
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"source": [
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"tsa_melted_holiday_travel.drop(columns='year').loc['2020'].assign(\n",
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" **{\n",
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" '7D MA': lambda x: x.travelers.rolling('7D').mean(),\n",
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" 'YTD mean': lambda x: x.travelers.expanding().mean()\n",
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" }\n",
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").plot(title='2020 TSA Traveler Throughput', ylabel='travelers', alpha=0.8)"
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"plot_data.plot(title='2020 TSA Traveler Throughput', ylabel='travelers', alpha=0.8)"
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]
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},
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{
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{
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"id": "babbc6d8-fff4-4505-ad88-8af332416208",
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"metadata": {},
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"outputs": [
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"5 74617773.0 7244733.0 NaN"
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"outputs": [
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{
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"text/plain": [
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