{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Showing uncertainty\n", "> Uncertainty occurs everywhere in data science, but it's frequently left out of visualizations where it should be included. Here, we review what a confidence interval is and how to visualize them for both single estimates and continuous functions. Additionally, we discuss the bootstrap resampling technique for assessing uncertainty and how to visualize it properly. This is the Summary of lecture \"Improving Your Data Visualizations in Python\", via datacamp.\n", "\n", "- toc: true \n", "- badges: true\n", "- comments: true\n", "- author: Chanseok Kang\n", "- categories: [Python, Datacamp, Visualization]\n", "- image: images/so2_compare.png" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "plt.rcParams['figure.figsize'] = (10, 5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Point estimate intervals\n", "- When is uncertainty important?\n", " - Estimates from sample\n", " - Average of a subset\n", " - Linear model coefficients\n", "- Why is uncertainty important?\n", " - Helps inform confidence in estimate\n", " - Neccessary for decision making\n", " - Acknowledges limitations of data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Basic confidence intervals\n", "You are a data scientist for a fireworks manufacturer in Des Moines, Iowa. You need to make a case to the city that your company's large fireworks show has not caused any harm to the city's air. To do this, you look at the average levels for pollutants in the week after the fourth of July and how they compare to readings taken after your last show. By showing confidence intervals around the averages, you can make a case that the recent readings were well within the normal range." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pollutantmeanstd_erryseen
0CO0.3519110.03356395% Interval0.40
1NO219.0214292.20051895% Interval16.00
2O30.0439820.00182295% Interval0.05
3SO20.2071430.03751895% Interval0.15
\n", "
" ], "text/plain": [ " pollutant mean std_err y seen\n", "0 CO 0.351911 0.033563 95% Interval 0.40\n", "1 NO2 19.021429 2.200518 95% Interval 16.00\n", "2 O3 0.043982 0.001822 95% Interval 0.05\n", "3 SO2 0.207143 0.037518 95% Interval 0.15" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "average_ests = pd.read_csv('./dataset/average_ests.csv', index_col=0)\n", "average_ests" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Construct CI bounds for averages\n", "average_ests['lower'] = average_ests['mean'] - 1.96 * average_ests['std_err']\n", "average_ests['upper'] = average_ests['mean'] + 1.96 * average_ests['std_err']\n", "\n", "# Setup a grid of plots, with non-shared x axes limits\n", "g = sns.FacetGrid(average_ests, row='pollutant', sharex=False, aspect=2);\n", "\n", "# Plot CI for average estimate\n", "g.map(plt.hlines, 'y', 'lower', 'upper');\n", "\n", "# Plot observed values for comparison and remove axes labels\n", "g.map(plt.scatter, 'seen', 'y', color='orangered').set_ylabels('').set_xlabels('');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This simple visualization shows that all the observed values fall well within the confidence intervals for all the pollutants except for $O_3$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Annotating confidence intervals\n", "Your data science work with pollution data is legendary, and you are now weighing job offers in both Cincinnati, Ohio and Indianapolis, Indiana. You want to see if the SO2 levels are significantly different in the two cities, and more specifically, which city has lower levels. To test this, you decide to look at the differences in the cities' SO2 values (Indianapolis' - Cincinnati's) over multiple years.\n", "\n", "Instead of just displaying a p-value for a significant difference between the cities, you decide to look at the 95% confidence intervals (columns `lower` and `upper`) of the differences. This allows you to see the magnitude of the differences along with any trends over the years." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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yearmeanstd_errlowerupper
020130.8408200.870135-0.8646452.546284
12014-1.3376250.761541-2.8302450.154996
22015-0.6493270.618175-1.8609500.562295
\n", "
" ], "text/plain": [ " year mean std_err lower upper\n", "0 2013 0.840820 0.870135 -0.864645 2.546284\n", "1 2014 -1.337625 0.761541 -2.830245 0.154996\n", "2 2015 -0.649327 0.618175 -1.860950 0.562295" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "diffs_by_year = pd.read_csv('./dataset/diffs_by_year.csv', index_col=0)\n", "diffs_by_year" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Set start and ends according to intervals\n", "# Make intervals thicker\n", "plt.hlines(y='year', xmin='lower', xmax='upper', \n", " linewidth=5, color='steelblue', alpha=0.7,\n", " data=diffs_by_year);\n", "\n", "# Point estimates\n", "plt.plot('mean', 'year', 'k|', data=diffs_by_year);\n", "\n", "# Add a 'null' reference line at 0 and color orangered\n", "plt.axvline(x=0, color='orangered', linestyle='--');\n", "\n", "# Set descriptive axis labels and title\n", "plt.xlabel('95% CI');\n", "plt.title('Avg SO2 differences between Cincinnati and Indianapolis');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By looking at the confidence intervals you can see that the difference flipped from generally positive (more pollution in Cincinnati) in 2013 to negative (more pollution in Indianapolis) in 2014 and 2015. Given that every year's confidence interval contains the null value of zero, no P-Value would be significant, and a plot that only showed significance would have been entirely hidden this trend." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Confidence bands" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Making a confidence band\n", "Vandenberg Air Force Base is often used as a location to launch rockets into space. You have a theory that a recent increase in the pace of rocket launches could be harming the air quality in the surrounding region. To explore this, you plotted a 25-day rolling average line of the measurements of atmospheric $NO_2$. To help decide if any pattern observed is random-noise or not, you decide to add a 99% confidence band around your rolling mean. Adding a confidence band to a trend line can help shed light on the stability of the trend seen. This can either increase or decrease the confidence in the discovered trend.\n", "\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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daymeanstd_err
0252.560.452831
1262.440.452831
2272.440.452831
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4292.400.452548
\n", "
" ], "text/plain": [ " day mean std_err\n", "0 25 2.56 0.452831\n", "1 26 2.44 0.452831\n", "2 27 2.44 0.452831\n", "3 28 2.44 0.452831\n", "4 29 2.40 0.452548" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "vandenberg_NO2 = pd.read_csv('./dataset/vandenberg_NO2.csv', index_col=0)\n", "vandenberg_NO2.head()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Draw 99% interval bands for average NO2\n", "vandenberg_NO2['lower'] = vandenberg_NO2['mean'] - 2.58 * vandenberg_NO2['std_err']\n", "vandenberg_NO2['upper'] = vandenberg_NO2['mean'] + 2.58 * vandenberg_NO2['std_err']\n", "\n", "# Plot mean estimate as a white semi-transparent line\n", "plt.plot('day', 'mean', data=vandenberg_NO2, color='white', alpha=0.4);\n", "\n", "# Fill between the upper and lower confidence band values\n", "plt.fill_between(x='day', y1='lower', y2='upper', data=vandenberg_NO2);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This plot shows that the middle of the year's $NO_2$ values are not only lower than the beginning and end of the year but also are less noisy. If just the moving average line were plotted, then this potentially interesting observation would be completely missed. (Can you think of what may cause reduced variance at the lower values of the pollutant?)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Separating a lot of bands\n", "It is relatively simple to plot a bunch of trend lines on top of each other for rapid and precise comparisons. Unfortunately, if you need to add uncertainty bands around those lines, the plot becomes very difficult to read. Figuring out whether a line corresponds to the top of one class' band or the bottom of another's can be hard due to band overlap. Luckily in Seaborn, it's not difficult to break up the overlapping bands into separate faceted plots.\n", "\n", "To see this, explore trends in SO2 levels for a few cities in the eastern half of the US. If you plot the trends and their confidence bands on a single plot - it's a mess. To fix, use Seaborn's `FacetGrid()` function to spread out the confidence intervals to multiple panes to ease your inspection." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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2Cincinnati268.94501.2813226.43360911.456391
3Cincinnati278.47751.3170595.89606511.058935
4Cincinnati289.23251.4163576.45644112.008559
\n", "
" ], "text/plain": [ " city day mean std_err lower upper\n", "0 Cincinnati 24 8.5150 1.297358 5.972178 11.057822\n", "1 Cincinnati 25 8.8825 1.277753 6.378104 11.386896\n", "2 Cincinnati 26 8.9450 1.281322 6.433609 11.456391\n", "3 Cincinnati 27 8.4775 1.317059 5.896065 11.058935\n", "4 Cincinnati 28 9.2325 1.416357 6.456441 12.008559" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "eastern_SO2 = pd.read_csv('./dataset/eastern_SO2.csv', index_col=0)\n", "eastern_SO2.head()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# setup a grid of plots with columns divided by location\n", "g = sns.FacetGrid(eastern_SO2, col='city', col_wrap=2);\n", "\n", "# Map interval plots to each cities data with coral colored ribbons\n", "g.map(plt.fill_between, 'day', 'lower', 'upper', color='coral');\n", "\n", "# Map overlaid mean plots with white line\n", "g.map(plt.plot, 'day', 'mean', color='white');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By separating each band into its own plot you can investigate each city with ease. Here, you see that Des Moines and Houston on average have lower SO2 values for the entire year than the two cities in the Midwest. Cincinnati has a high and variable peak near the beginning of the year but is generally more stable and lower than Indianapolis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Cleaning up bands for overlaps\n", "You are working for the city of Denver, Colorado and want to run an ad campaign about how much cleaner Denver's air is than Long Beach, California's air. To investigate this claim, you will compare the SO2 levels of both cities for the year 2014. Since you are solely interested in how the cities compare, you want to keep the bands on the same plot. To make the bands easier to compare, decrease the opacity of the confidence bands and set a clear legend." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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citydaymeanstd_errlowerupper
0Denver202.58000.4107221.7749853.385015
1Denver212.61250.4056611.8174043.407596
2Denver222.67750.4175451.8591133.495887
3Denver232.65250.4193821.8305123.474488
4Denver242.75250.4169601.9352583.569742
\n", "
" ], "text/plain": [ " city day mean std_err lower upper\n", "0 Denver 20 2.5800 0.410722 1.774985 3.385015\n", "1 Denver 21 2.6125 0.405661 1.817404 3.407596\n", "2 Denver 22 2.6775 0.417545 1.859113 3.495887\n", "3 Denver 23 2.6525 0.419382 1.830512 3.474488\n", "4 Denver 24 2.7525 0.416960 1.935258 3.569742" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "SO2_compare = pd.read_csv('./dataset/SO2_compare.csv', index_col=0)\n", "SO2_compare.head()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for city, color in [('Denver', '#66c2a5'), ('Long Beach', '#fc8d62')]:\n", " # Filter data to desired city\n", " city_data = SO2_compare[SO2_compare.city == city]\n", " \n", " # Set city interval color to desired and lower opacity\n", " plt.fill_between(x='day', y1='lower', y2='upper', data=city_data, color=color, alpha=0.4);\n", " \n", " # Draw a faint mean line for reference and give a label for legend\n", " plt.plot('day', 'mean', data=city_data, label=city, color=color, alpha=0.25);\n", " \n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From these two curves you can see that during the first half of the year Long Beach generally has a higher average SO2 value than Denver, in the middle of the year they are very close, and at the end of the year Denver seems to have higher averages. However, by showing the confidence intervals, you can see however that almost none of the year shows a statistically meaningful difference in average values between the two cities." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Beyond 95%\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 90, 95, and 99% intervals\n", "You are a data scientist for an outdoor adventure company in Fairbanks, Alaska. Recently, customers have been having issues with SO2 pollution, leading to costly cancellations. The company has sensors for CO, NO2, and O3 but not SO2 levels.\n", "\n", "You've built a model that predicts SO2 values based on the values of pollutants with sensors (loaded as `pollution_model`, a `statsmodels` object). You want to investigate which pollutant's value has the largest effect on your model's SO2 prediction. This will help you know which pollutant's values to pay most attention to when planning outdoor tours. To maximize the amount of information in your report, show multiple levels of uncertainty for the model estimates." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "from statsmodels.formula.api import ols" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "pollution = pd.read_csv('./dataset/pollution_wide.csv')\n", "pollution = pollution.query(\"city == 'Fairbanks' & year == 2014 & month == 11\")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "pollution_model = ols(formula='SO2 ~ CO + NO2 + O3 + day', data=pollution)\n", "res = pollution_model.fit()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Add interval percent widths\n", "alphas = [ 0.01, 0.05, 0.1] \n", "widths = [ '99% CI', '95%', '90%']\n", "colors = ['#fee08b','#fc8d59','#d53e4f']\n", "\n", "for alpha, color, width in zip(alphas, colors, widths):\n", " # Grab confidence interval\n", " conf_ints = res.conf_int(alpha)\n", " \n", " # Pass current interval color and legend label to plot\n", " plt.hlines(y = conf_ints.index, xmin = conf_ints[0], xmax = conf_ints[1],\n", " colors = color, label = width, linewidth = 10) \n", "\n", "# Draw point estimates\n", "plt.plot(res.params, res.params.index, 'wo', label = 'Point Estimate')\n", "\n", "plt.legend(loc = 'upper right')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 90 and 95% bands\n", "You are looking at a 40-day rolling average of the $NO_2$ pollution levels for the city of Cincinnati in 2013. To provide as detailed a picture of the uncertainty in the trend you want to look at both the 90 and 99% intervals around this rolling estimate.\n", "\n", "To do this, set up your two interval sizes and an orange ordinal color palette. Additionally, to enable precise readings of the bands, make them semi-transparent, so the Seaborn background grids show through." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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daymeanstd_err
08225.4251.447795
18325.2501.429051
28425.4251.435656
38525.2751.454728
48625.0251.438092
\n", "
" ], "text/plain": [ " day mean std_err\n", "0 82 25.425 1.447795\n", "1 83 25.250 1.429051\n", "2 84 25.425 1.435656\n", "3 85 25.275 1.454728\n", "4 86 25.025 1.438092" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cinci_13_no2 = pd.read_csv('./dataset/cinci_13_no2.csv', index_col=0);\n", "cinci_13_no2.head()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "int_widths = ['90%', '99%']\n", "z_scores = [1.67, 2.58]\n", "colors = ['#fc8d59', '#fee08b']\n", "\n", "for percent, Z, color in zip(int_widths, z_scores, colors):\n", " \n", " # Pass lower and upper confidence bounds and lower opacity\n", " plt.fill_between(\n", " x = cinci_13_no2.day, alpha = 0.4, color = color,\n", " y1 = cinci_13_no2['mean'] - Z * cinci_13_no2['std_err'],\n", " y2 = cinci_13_no2['mean'] + Z * cinci_13_no2['std_err'],\n", " label = percent);\n", " \n", "plt.legend();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This plot shows us that throughout 2013, the average NO2 values in Cincinnati followed a cyclical pattern with the seasons. However, the uncertainty bands show that for most of the year you can't be sure this pattern is not noise at both a 90 and 99% confidence level." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Using band thickness instead of coloring\n", "You are a researcher investigating the elevation a rocket reaches before visual is lost and pollutant levels at Vandenberg Air Force Base. You've built a model to predict this relationship, and since you are working independently, you don't have the money to pay for color figures in your journal article. You need to make your model results plot work in black and white. To do this, you will plot the 90, 95, and 99% intervals of the effect of each pollutant as successively smaller bars." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pollutanteststd_err
0SO20.1381850.034651
1NO20.3201210.049849
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\n", "
" ], "text/plain": [ " pollutant est std_err\n", "0 SO2 0.138185 0.034651\n", "1 NO2 0.320121 0.049849\n", "2 CO 0.084282 0.024758\n", "3 O3 0.565368 0.022191" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rocket_model = pd.read_csv('./dataset/rocket_model.csv', index_col=0)\n", "rocket_model" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Decrase interval thickness as interval widens\n", "sizes = [ 15, 10, 5]\n", "int_widths = ['90% CI', '95%', '99%']\n", "z_scores = [ 1.67, 1.96, 2.58]\n", "\n", "for percent, Z, size in zip(int_widths, z_scores, sizes):\n", " plt.hlines(y = rocket_model.pollutant, \n", " xmin = rocket_model['est'] - Z * rocket_model['std_err'],\n", " xmax = rocket_model['est'] + Z * rocket_model['std_err'],\n", " label = percent, \n", " # Resize lines and color them gray\n", " linewidth = size, \n", " color = 'gray'); \n", " \n", "# Add point estimate\n", "plt.plot('est', 'pollutant', 'wo', data = rocket_model, label = 'Point Estimate');\n", "plt.legend(loc = 'center left', bbox_to_anchor = (1, 0.5));" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "While less elegant than using color to differentiate interval sizes, this plot still clearly allows the reader to access the effect each pollutant has on rocket visibility. You can see that of all the pollutants, O3 has the largest effect and also the tightest confidence bounds" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualizing the bootstrap\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### The bootstrap histogram\n", "You are considering a vacation to Cincinnati in May, but you have a severe sensitivity to NO2. You pull a few years of pollution data from Cincinnati in May and look at a bootstrap estimate of the average $NO_2$ levels. You only have one estimate to look at the best way to visualize the results of your bootstrap estimates is with a histogram.\n", "\n", "While you like the intuition of the bootstrap histogram by itself, your partner who will be going on the vacation with you, likes seeing percent intervals. To accommodate them, you decide to highlight the 95% interval by shading the region." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "# Perform bootstrapped mean on a vector\n", "def bootstrap(data, n_boots):\n", " return [np.mean(np.random.choice(data,len(data))) for _ in range(n_boots) ]" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pollution = pd.read_csv('./dataset/pollution_wide.csv')\n", "cinci_may_NO2 = pollution.query(\"city == 'Cincinnati' & month == 5\").NO2\n", "\n", "# Generate bootstrap samples\n", "boot_means = bootstrap(cinci_may_NO2, 1000)\n", "\n", "# Get lower and upper 95% interval bounds\n", "lower, upper = np.percentile(boot_means, [2.5, 97.5])\n", "\n", "# Plot shaded area for interval\n", "plt.axvspan(lower, upper, color = 'gray', alpha = 0.2);\n", "\n", "# Draw histogram of bootstrap samples\n", "sns.distplot(boot_means, bins = 100, kde = False);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Your bootstrap histogram looks stable and uniform. You're now confident that the average NO2 levels in Cincinnati during your vacation should be in the range of 16 to 23." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Bootstrapped regressions\n", "While working for the Long Beach parks and recreation department investigating the relationship between $NO_2$ and $SO_2$ you noticed a cluster of potential outliers that you suspect might be throwing off the correlations.\n", "\n", "Investigate the uncertainty of your correlations through bootstrap resampling to see how stable your fits are. For convenience, the bootstrap sampling is complete and is provided as `no2_so2_boot` along with `no2_so2` for the non-resampled data." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "no2_so2 = pd.read_csv('./dataset/no2_so2.csv', index_col=0)\n", "no2_so2_boot = pd.read_csv('./dataset/no2_so2_boot.csv', index_col=0)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.lmplot('NO2', 'SO2', data = no2_so2_boot,\n", " # Tell seaborn to a regression line for each sample\n", " hue = 'sample', \n", " # Make lines blue and transparent\n", " line_kws = {'color': 'steelblue', 'alpha': 0.2},\n", " # Disable built-in confidence intervals\n", " ci = None, legend = False, scatter = False);\n", "\n", "# Draw scatter of all points\n", "plt.scatter('NO2', 'SO2', data = no2_so2);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The outliers appear to drag down the regression lines as evidenced by the cluster of lines with more severe slopes than average. In a single plot, you have not only gotten a good idea of the variability of your correlation estimate but also the potential effects of outliers." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Lots of bootstraps with beeswarms\n", "As a current resident of Cincinnati, you're curious to see how the average NO2 values compare to Des Moines, Indianapolis, and Houston: a few other cities you've lived in.\n", "\n", "To look at this, you decide to use bootstrap estimation to look at the mean NO2 values for each city. Because the comparisons are of primary interest, you will use a swarm plot to compare the estimates." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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cityyearmonthdayCONO2O3SO2
136Cincinnati201351210.64033.00.0551.85
137Cincinnati201351220.31523.00.0434.10
138Cincinnati201351230.26013.00.0394.75
139Cincinnati201351240.24517.00.0514.45
140Cincinnati201351250.23012.00.0320.85
...........................
8673Vandenberg Air Force Base201551370.0001.00.0440.50
8674Vandenberg Air Force Base201551380.0002.00.0431.00
8675Vandenberg Air Force Base201551390.0000.00.0410.50
8676Vandenberg Air Force Base201551400.0000.00.0440.50
8677Vandenberg Air Force Base201551410.0000.00.0410.50
\n", "

736 rows × 8 columns

\n", "
" ], "text/plain": [ " city year month day CO NO2 O3 SO2\n", "136 Cincinnati 2013 5 121 0.640 33.0 0.055 1.85\n", "137 Cincinnati 2013 5 122 0.315 23.0 0.043 4.10\n", "138 Cincinnati 2013 5 123 0.260 13.0 0.039 4.75\n", "139 Cincinnati 2013 5 124 0.245 17.0 0.051 4.45\n", "140 Cincinnati 2013 5 125 0.230 12.0 0.032 0.85\n", "... ... ... ... ... ... ... ... ...\n", "8673 Vandenberg Air Force Base 2015 5 137 0.000 1.0 0.044 0.50\n", "8674 Vandenberg Air Force Base 2015 5 138 0.000 2.0 0.043 1.00\n", "8675 Vandenberg Air Force Base 2015 5 139 0.000 0.0 0.041 0.50\n", "8676 Vandenberg Air Force Base 2015 5 140 0.000 0.0 0.044 0.50\n", "8677 Vandenberg Air Force Base 2015 5 141 0.000 0.0 0.041 0.50\n", "\n", "[736 rows x 8 columns]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pollution_may = pollution.query(\"month == 5\")\n", "pollution_may" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Initialize a holder DataFrame for bootstrap results\n", "city_boots = pd.DataFrame()\n", "\n", "for city in ['Cincinnati', 'Des Moines', 'Indianapolis', 'Houston']:\n", " # Filter to city\n", " city_NO2 = pollution_may[pollution_may.city == city].NO2\n", " # Bootstrap city data & put in DataFrame\n", " cur_boot = pd.DataFrame({'NO2_avg': bootstrap(city_NO2, 100), 'city': city})\n", " # Append to other city's bootstraps\n", " city_boots = pd.concat([city_boots,cur_boot])\n", "\n", "# Beeswarm plot of averages with citys on y axis\n", "sns.swarmplot(y = \"city\", x = \"NO2_avg\", data = city_boots, color = 'coral');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The beeswarm plots show that Indianapolis and Houston both have the highest average NO2 values, with Cincinnati falling roughly in the middle. Interestingly, you can rather confidently say that Des Moines has the lowest as nearly all its sample estimates fall below those of the other cities." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }