diff --git a/notebooks/covidtracking-dashboard.ipynb b/notebooks/covidtracking-dashboard.ipynb deleted file mode 100644 index 6f9f6e623cd7c31cc77f3e6139efaf4fc08233d2..0000000000000000000000000000000000000000 --- a/notebooks/covidtracking-dashboard.ipynb +++ /dev/null @@ -1,474 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from pathlib import Path\n", - "\n", - "import pandas as pd\n", - "import altair as alt\n", - "from IPython.display import display, HTML\n", - "\n", - "from covid_19_utils.converters import CaseConverter" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "html_credits=HTML('''\n", - "<p style=\"font-size: smaller\">Data Sources: \n", - " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", - "<br>\n", - "Analysis and Visualization:\n", - " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", - "</p>''')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "tags": [ - "parameters" - ] - }, - "outputs": [], - "source": [ - "data_path = '../data/covidtracking'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# read in the data \n", - "converter = CaseConverter('../data/atlas')\n", - "data_df = converter.read_convert(data_path)\n", - "\n", - "# referring to \"state\" will make more sense in this notebook\n", - "data_df = data_df.rename(columns={\"region_label\": \"state\"})" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Compute daily differences\n", - "tdf = data_df.sort_values(['state', 'date'], ascending=[True, False]).set_index(['state', 'date'])\n", - "diffs_df = tdf[['positive', 'deceased', 'positive_100k', 'deceased_100k']].groupby(level='state').diff(periods=-1).dropna(how='all')\n", - "tdf_diff=tdf.join(diffs_df, rsuffix='_diff').reset_index()\n", - "\n", - "# \"Normalizing\" the total tests\n", - "tdf_diff['total_10'] = tdf_diff['tested']/10.\n", - "\n", - "# Daily totals\n", - "daily_totals = tdf_diff.groupby('date').sum()\n", - "daily_totals.reset_index(level=0, inplace=True)\n", - "\n", - "# National daily totals\n", - "nation_df = data_df.groupby('date').sum()\n", - "nation_df['state']='All US'\n", - "nation_df = nation_df.reset_index()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Covid-19 Cases in U.S.\n", - "\n", - "The case data from the U.S. is obtained from https://covidtracking.com, a public crowd-sourced covid-19 dataset. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Growth trends" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# make dataframe for text labels on chart - hand edit these label locations\n", - "textLabels_df = pd.DataFrame(\n", - " [[10,6000,'doubles every day'],\n", - " [36,50000,'doubles every 3 days'],\n", - " [34,100, 'doubles every week']],\n", - " columns =['labelX', 'labelY','labelText']\n", - ")\n", - "\n", - "# make dataframe of states with points >=10 deceaseds\n", - "deceased10_df = data_df.loc[data_df['deceased']>=10]\n", - "\n", - "# group deceased10 dataframe by state and then increasing order of date\n", - "deceased10_df = deceased10_df.sort_values(by=['state','date'])\n", - "\n", - "# add US to that dataframe\n", - "nationdeceased10_df = nation_df.loc[nation_df['deceased']>=10]\n", - "deceased10_df= pd.concat ([deceased10_df,nationdeceased10_df])\n", - "\n", - "deceased10_df = deceased10_df.reset_index()\n", - "\n", - "# make a list of the states with 10 or more deceaseds\n", - "state_list = list(set(deceased10_df['state']))\n", - "\n", - "# add a column for the number of days since the 10th deceased for each state\n", - "for state, df in deceased10_df.groupby('state'):\n", - " deceased10_df.loc[df.index,'sinceDay0'] = range(0, len(df))\n", - "deceased10_df = deceased10_df.astype({'sinceDay0': 'int32'})\n", - "\n", - "#Now create plotlines for each state since 10 deceaseds\n", - "lineChart = alt.Chart(deceased10_df,title='US States: Cumulative Deaths Since 10th Death').mark_line(interpolate='basis').encode(\n", - " alt.X('sinceDay0:Q', axis=alt.Axis(title='Days Since 10th Death')),\n", - " alt.Y('deceased:Q',\n", - " axis = alt.Axis(title='Cumulative Deaths'),\n", - " scale=alt.Scale(type='log')),\n", - " tooltip=['state', 'sinceDay0', 'deceased', 'positive'],\n", - " color = 'state'\n", - ").properties(width=800,height=400)\n", - "\n", - "## Create a layer with the lines for doubling every day and doubling every week\n", - "\n", - "# Compute theoretical trends of doubling every day, 3 days, week\n", - "days = {'day':[1,2,3,4,5,10,15,20, max(deceased10_df.sinceDay0)+5]}\n", - "startCase = 10\n", - "logRuleDay_df = pd.DataFrame(days, columns=['day'])\n", - "logRuleDay_df['case']= startCase * pow(2,logRuleDay_df['day'])\n", - "logRuleDay_df['doubling period']='every day'\n", - "\n", - "logRule3Days_df = pd.DataFrame(days, columns=['day'])\n", - "logRule3Days_df['case']= startCase * pow(2,(logRule3Days_df['day'])/3)\n", - "logRule3Days_df['doubling period']='three days'\n", - "\n", - "logRuleWeek_df = pd.DataFrame(days, columns=['day'])\n", - "logRuleWeek_df['case']= startCase * pow(2,(logRuleWeek_df['day'])/7)\n", - "logRuleWeek_df['doubling period']='every week'\n", - "\n", - "logRules_df = pd.concat([logRuleDay_df, logRule3Days_df, logRuleWeek_df])\n", - "logRules_df = logRules_df.reset_index()\n", - "\n", - "\n", - "ruleChart = alt.Chart(logRules_df).mark_line(opacity=0.2,clip=True).encode(\n", - " alt.X('day:Q',\n", - " scale=alt.Scale(domain=[1,max(deceased10_df.sinceDay0)+5])),\n", - " alt.Y('case', scale=alt.Scale(type='log',domain=[10,15000]),\n", - " ),\n", - " color = 'doubling period',\n", - " tooltip = ['doubling period']) \n", - "\n", - "# create a layer for the state labels\n", - "# 1) make dataframe with each state's max days\n", - "# 2) make a chart layer with text of state name to right of each state's rightmost point\n", - "stateLabels_df = deceased10_df[deceased10_df['sinceDay0'] == deceased10_df.groupby(['state'])['sinceDay0'].transform(max)]\n", - "labelChart = alt.Chart(stateLabels_df).mark_text(align='left', baseline='middle', dx=10).encode(\n", - " x='sinceDay0',\n", - " y='deceased',\n", - " text='state',\n", - " color='state')\n", - "\n", - "#now put the text labels layer on top of state labels Chart\n", - "labelChart = labelChart + alt.Chart(textLabels_df).mark_text(align='right', baseline='bottom', dx=0, size=18,opacity=0.5).encode(\n", - " x='labelX',\n", - " y='labelY',\n", - " text='labelText')\n", - "\n", - "\n", - "## Create some tooltip behavior - show Y values on mouseover\n", - "# Step 1: Selection that chooses nearest point based on value on x-axis\n", - "nearest = alt.selection(type='single', nearest=True, on='mouseover',\n", - " fields=['sinceDay0'])\n", - "\n", - "# Step 2: Transparent selectors across the chart. This is what tells us\n", - "# the x-value of the cursor\n", - "selectors = alt.Chart().mark_point().encode(\n", - " x=\"sinceDay0:Q\",\n", - " opacity=alt.value(0),\n", - ").add_selection(\n", - " nearest\n", - ")\n", - "\n", - "# Step 3: Add text, show values in column when it's the nearest point to \n", - "# mouseover, else show blank\n", - "text = lineChart.mark_text(align='center', dx=3, dy=-20).encode(\n", - " text=alt.condition(nearest, 'deceased', alt.value(' '))\n", - ")\n", - "\n", - "\n", - "#Finally, lets show the chart!\n", - "\n", - "chart = alt.layer(lineChart, ruleChart, labelChart, selectors, text, data=deceased10_df)\n", - "\n", - "display(chart)\n", - "display(html_credits)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# make dataframe for text labels on chart - hand edit these label locations\n", - "textLabels_df = pd.DataFrame(\n", - " [[9,30000,'doubles every day'],\n", - " [28,31000,'doubles every 3 days'],\n", - " [32,1000, 'doubles every week']],\n", - " columns =['labelX', 'labelY','labelText']\n", - ")\n", - "\n", - "# make dataframe with only points >=100 positives\n", - "positive100_df = data_df.loc[data_df['positive']>=100]\n", - "\n", - "## add US to that dataframe\n", - "nationpos100_df = nation_df.loc[nation_df['positive']>=100]\n", - "positive100_df= pd.concat ([positive100_df,nationpos100_df])\n", - "\n", - "# group positive100 dataframe by state and then increasing order of date\n", - "positive100_df = positive100_df.sort_values(by=['state','date'])\n", - "positive100_df = positive100_df.reset_index()\n", - "\n", - "# make a list of the states with 10 or more deaths (don't really need this)\n", - "# state_list = list(set(positive100_df['state']))\n", - "\n", - "# add a column for the number of days since the 100th case for each state\n", - "for state, df in positive100_df.groupby('state'):\n", - " positive100_df.loc[df.index,'sinceDay0'] = range(0, len(df))\n", - "positive100_df = positive100_df.astype({'sinceDay0': 'int32'})\n", - "\n", - " \n", - "# Now create plotlines for each state since 10 deaths\n", - "lineChart = alt.Chart(positive100_df, title=\"US States: total cases since 100th case\").mark_line(interpolate='basis').encode(\n", - " alt.X('sinceDay0:Q', axis=alt.Axis(title='Days since 100th case')),\n", - " alt.Y('positive:Q',\n", - " axis = alt.Axis(title='Cumulative positive cases'),\n", - " scale=alt.Scale(type='log')),\n", - " tooltip=['state', 'sinceDay0', 'deceased', 'positive'],\n", - " color = 'state'\n", - ").properties(width=800,height=400)\n", - "\n", - "## Create a layer with the lines for doubling every day and doubling every week\n", - "# make dataframe with lines to indicate doubling every day, 3 days, week \n", - "\n", - "days = {'day':[1,2,3,4,5,10,15,20, max(positive100_df.sinceDay0)+5]}\n", - "startCase = 100\n", - "logRuleDay_df = pd.DataFrame (days, columns=['day'])\n", - "logRuleDay_df['case']= startCase * pow(2,logRuleDay_df['day'])\n", - "logRuleDay_df['doubling period']='every day'\n", - "\n", - "logRule3Days_df = pd.DataFrame (days, columns=['day'])\n", - "logRule3Days_df['case']= startCase * pow(2,(logRule3Days_df['day'])/3)\n", - "logRule3Days_df['doubling period']='three days'\n", - "\n", - "logRuleWeek_df = pd.DataFrame (days, columns=['day'])\n", - "logRuleWeek_df['case']= startCase * pow(2,(logRuleWeek_df['day'])/7)\n", - "logRuleWeek_df['doubling period']='every week'\n", - "\n", - "logRules_df = pd.concat([logRuleDay_df, logRule3Days_df, logRuleWeek_df])\n", - "logRules_df = logRules_df.reset_index()\n", - "\n", - "ruleChart = alt.Chart(logRules_df).mark_line(opacity=0.2,clip=True).encode(\n", - " alt.X('day:Q',\n", - " scale=alt.Scale(domain=[1, max(positive100_df.sinceDay0)+5])),\n", - " alt.Y('case', scale=alt.Scale(domain=[100,200000], type='log'),\n", - " ),\n", - " color = 'doubling period')\n", - "\n", - "# create a layer for the state labels\n", - "# 1) make dataframe with each state's max days\n", - "# 2) make a chart layer with text of state name to right of each state's rightmost point\n", - "stateLabels_df = positive100_df[positive100_df['sinceDay0'] == positive100_df.groupby(['state'])['sinceDay0'].transform(max)]\n", - "labelChart = alt.Chart(stateLabels_df).mark_text(align='left', baseline='middle', dx=10).encode(\n", - " x='sinceDay0',\n", - " y='positive',\n", - " text='state',\n", - " color='state')\n", - "\n", - "#now put the text labels layer on top of state labels Chart\n", - "labelChart = labelChart + alt.Chart(textLabels_df).mark_text(align='right', baseline='bottom', dx=0, size=18,opacity=0.5).encode(\n", - " x='labelX',\n", - " y='labelY',\n", - " text='labelText')\n", - "\n", - "#Create some tooltip behavior\n", - "# Step 1: Selection that chooses nearest point based on value on x-axis\n", - "nearest = alt.selection(type='single', nearest=True, on='mouseover',\n", - " fields=['sinceDay0'])\n", - "\n", - "# Step 2: Transparent selectors across the chart. This is what tells us\n", - "# the x-value of the cursor\n", - "selectors = alt.Chart().mark_point().encode(\n", - " x=\"sinceDay0:Q\",\n", - " opacity=alt.value(0),\n", - ").add_selection(\n", - " nearest\n", - ")\n", - "\n", - "# Step 3: Add text, show values in Sex column when it's the nearest point to \n", - "# mouseover, else show blank\n", - "text = lineChart.mark_text(align='center', dx=3, dy=-20).encode(\n", - " text=alt.condition(nearest, 'positive', alt.value(' '))\n", - ")\n", - "\n", - "\n", - "#Finally, lets show the chart!\n", - "\n", - "chart = alt.layer(lineChart, ruleChart, labelChart, selectors, text, data=positive100_df)\n", - "#chart = alt.layer(lineChart, ruleChart, labelChart)\n", - "chart.properties (width=400,height=800)\n", - "display(chart)\n", - "display(html_credits)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Daily Cumulative Totals\n", - "\n", - "Cumulative reported totals of positive cases and deaths. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "base = alt.Chart(\n", - " daily_totals\n", - ").mark_bar(size=7).encode(\n", - " alt.X('date', axis=alt.Axis(title='')\n", - " )\n", - ").properties(\n", - " height=200,\n", - " width=400\n", - ")\n", - "\n", - "cumulative = base.encode(alt.Y('positive', title = 'Cumulative cases'))\n", - "cumulative_deaths = base.encode(alt.Y('deceased', title = 'Cumulative deaths'))\n", - "rates = base.encode(alt.Y('positive_diff', title='Daily cases'))\n", - "rates_deaths = base.encode(alt.Y('deceased_diff', title='Daily deaths'))\n", - "chart = alt.vconcat(\n", - " cumulative | rates, cumulative_deaths | rates_deaths,\n", - " title='Cumulative Covid-19 cases and deaths in the U.S.'\n", - ").configure_title(\n", - " anchor='middle'\n", - ")\n", - "display(chart)\n", - "display(html_credits)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Total tests and positives per 100k population" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "most_recent_test_date = data_df['date'].max()\n", - "most_recent_df = data_df[data_df['date'] == most_recent_test_date]\n", - "print(\"Most recent test date\", most_recent_test_date)\n", - "print(len(most_recent_df), \"states/territories have data on this date.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "viz_df = most_recent_df.sort_values('tested_100k', ascending=False)\n", - "chart = alt.Chart(viz_df, title=\"Cases (orange points) and tests(blue bars) per 100k\").encode(alt.X('state', sort=None))\n", - "tests = chart.mark_bar().encode(alt.Y('tested_100k', axis=alt.Axis(title='COVID-19 Tests/100k, Positive Cases/100k')))\n", - "positives = chart.mark_point(color='orange', filled=True, size=100, opacity=1).encode(alt.Y('positive_100k'))\n", - "display(alt.layer(tests, positives))\n", - "display(html_credits)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Counts and rates by state\n", - "\n", - "Taking a look at the three states with the highest per-capita incidence of covid-19. The red and yellow curves represent the total tests and total positive tests respectively. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# produce the charts for a few states\n", - "\n", - "charts=[]\n", - "for state in most_recent_df.sort_values('tested_100k', ascending=False)['state'].to_list()[:3]: \n", - " state_df = tdf_diff[tdf_diff['state'] == state].copy()\n", - "\n", - " base = alt.Chart(state_df, title=state).encode(alt.X('date', axis=alt.Axis(title='Date'))).properties(width=250, height=150)\n", - " dailies = base.mark_bar(size=6).encode(alt.Y('positive_diff', axis=alt.Axis(title='Daily positive')))\n", - "\n", - " totals = base.mark_line(color='red').encode(alt.Y('total_10', axis=alt.Axis(title='Total/10'))) \n", - " positives = totals.mark_line(color='orange').encode(alt.Y('positive', axis=alt.Axis(title='Positive')))\n", - " cumulative = totals + positives\n", - "\n", - " ratio = base.mark_line(color='red').encode(alt.Y('ratio', axis=alt.Axis(title='Positive/Total'), scale=alt.Scale(domain=(0,1))))\n", - " \n", - " charts.append(alt.layer(dailies, cumulative).resolve_scale(y='independent'))\n", - "\n", - "display(alt.hconcat(*charts))\n", - "display(html_credits)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "hide_input": true, - "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": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/notebooks/covidtracking.ipynb b/notebooks/covidtracking.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b6d4078c76ba4d982796cf4d1ff97e5c34dc064d --- /dev/null +++ b/notebooks/covidtracking.ipynb @@ -0,0 +1,869 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "\n", + "import pandas as pd\n", + "import altair as alt\n", + "from IPython.display import display, HTML\n", + "\n", + "from covid_19_utils.converters import CaseConverter" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "html_credits=HTML('''\n", + "<p style=\"font-size: smaller\">Data Sources: \n", + " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", + "<br>\n", + "Analysis and Visualization:\n", + " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", + "</p>''')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [ + "parameters" + ] + }, + "outputs": [], + "source": [ + "data_path = '../data/covidtracking'\n", + "atlas_path = '../data/atlas'" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# read in the data \n", + "converter = CaseConverter(atlas_path)\n", + "data_df = converter.read_convert(data_path)\n", + "\n", + "# referring to \"state\" will make more sense in this notebook\n", + "data_df = data_df.rename(columns={\"region_label\": \"state\"})" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Compute daily differences\n", + "tdf = data_df.sort_values(['state', 'date'], ascending=[True, False]).set_index(['state', 'date'])\n", + "diffs_df = tdf[['positive', 'deceased', 'positive_100k', 'deceased_100k']].groupby(level='state').diff(periods=-1).dropna(how='all')\n", + "tdf_diff=tdf.join(diffs_df, rsuffix='_diff').reset_index()\n", + "\n", + "# \"Normalizing\" the total tests\n", + "tdf_diff['total_10'] = tdf_diff['tested']/10.\n", + "\n", + "# Daily totals\n", + "daily_totals = tdf_diff.groupby('date').sum()\n", + "daily_totals.reset_index(level=0, inplace=True)\n", + "\n", + "# National daily totals\n", + "nation_df = data_df.groupby('date').sum()\n", + "nation_df['state']='All US'\n", + "nation_df = nation_df.reset_index()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Covid-19 Cases in U.S.\n", + "\n", + "The case data from the U.S. is obtained from https://covidtracking.com, a public crowd-sourced covid-19 dataset. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Growth trends" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "<div id=\"altair-viz-51055dfdc5e74ae0a4ff8cb0b78c31d8\"></div>\n", + "<script type=\"text/javascript\">\n", + " (function(spec, embedOpt){\n", + " const outputDiv = document.getElementById(\"altair-viz-51055dfdc5e74ae0a4ff8cb0b78c31d8\");\n", + " const paths = {\n", + " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", + " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", + " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", + " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", + " };\n", + "\n", + " function loadScript(lib) {\n", + " return new Promise(function(resolve, reject) {\n", + " var s = document.createElement('script');\n", + " s.src = paths[lib];\n", + " s.async = true;\n", + " s.onload = () => resolve(paths[lib]);\n", + " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", + " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", + " });\n", + " }\n", + "\n", + " function showError(err) {\n", + " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", + " throw err;\n", + " }\n", + "\n", + " function displayChart(vegaEmbed) {\n", + " vegaEmbed(outputDiv, spec, embedOpt)\n", + " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", + "<br>\n", + "Analysis and Visualization:\n", + " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", + "</p>" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# make dataframe for text labels on chart - hand edit these label locations\n", + "textLabels_df = pd.DataFrame(\n", + " [[10,6000,'doubles every day'],\n", + " [36,50000,'doubles every 3 days'],\n", + " [34,100, 'doubles every week']],\n", + " columns =['labelX', 'labelY','labelText']\n", + ")\n", + "\n", + "# make dataframe of states with points >=10 deceaseds\n", + "deceased10_df = data_df.loc[data_df['deceased']>=10]\n", + "\n", + "# group deceased10 dataframe by state and then increasing order of date\n", + "deceased10_df = deceased10_df.sort_values(by=['state','date'])\n", + "\n", + "# add US to that dataframe\n", + "nationdeceased10_df = nation_df.loc[nation_df['deceased']>=10]\n", + "deceased10_df= pd.concat ([deceased10_df,nationdeceased10_df])\n", + "\n", + "deceased10_df = deceased10_df.reset_index()\n", + "\n", + "# make a list of the states with 10 or more deceaseds\n", + "state_list = list(set(deceased10_df['state']))\n", + "\n", + "# add a column for the number of days since the 10th deceased for each state\n", + "for state, df in deceased10_df.groupby('state'):\n", + " deceased10_df.loc[df.index,'sinceDay0'] = range(0, len(df))\n", + "deceased10_df = deceased10_df.astype({'sinceDay0': 'int32'})\n", + "\n", + "#Now create plotlines for each state since 10 deceaseds\n", + "lineChart = alt.Chart(deceased10_df,title='US States: Cumulative Deaths Since 10th Death').mark_line(interpolate='basis').encode(\n", + " alt.X('sinceDay0:Q', axis=alt.Axis(title='Days Since 10th Death')),\n", + " alt.Y('deceased:Q',\n", + " axis = alt.Axis(title='Cumulative Deaths'),\n", + " scale=alt.Scale(type='log')),\n", + " tooltip=['state', 'sinceDay0', 'deceased', 'positive'],\n", + " color = 'state'\n", + ").properties(width=800,height=400)\n", + "\n", + "## Create a layer with the lines for doubling every day and doubling every week\n", + "\n", + "# Compute theoretical trends of doubling every day, 3 days, week\n", + "days = {'day':[1,2,3,4,5,10,15,20, max(deceased10_df.sinceDay0)+5]}\n", + "startCase = 10\n", + "logRuleDay_df = pd.DataFrame(days, columns=['day'])\n", + "logRuleDay_df['case']= startCase * pow(2,logRuleDay_df['day'])\n", + "logRuleDay_df['doubling period']='every day'\n", + "\n", + "logRule3Days_df = pd.DataFrame(days, columns=['day'])\n", + "logRule3Days_df['case']= startCase * pow(2,(logRule3Days_df['day'])/3)\n", + "logRule3Days_df['doubling period']='three days'\n", + "\n", + "logRuleWeek_df = pd.DataFrame(days, columns=['day'])\n", + "logRuleWeek_df['case']= startCase * pow(2,(logRuleWeek_df['day'])/7)\n", + "logRuleWeek_df['doubling period']='every week'\n", + "\n", + "logRules_df = pd.concat([logRuleDay_df, logRule3Days_df, logRuleWeek_df])\n", + "logRules_df = logRules_df.reset_index()\n", + "\n", + "\n", + "ruleChart = alt.Chart(logRules_df).mark_line(opacity=0.2,clip=True).encode(\n", + " alt.X('day:Q',\n", + " scale=alt.Scale(domain=[1,max(deceased10_df.sinceDay0)+5])),\n", + " alt.Y('case', scale=alt.Scale(type='log',domain=[10,15000]),\n", + " ),\n", + " color = 'doubling period',\n", + " tooltip = ['doubling period']) \n", + "\n", + "# create a layer for the state labels\n", + "# 1) make dataframe with each state's max days\n", + "# 2) make a chart layer with text of state name to right of each state's rightmost point\n", + "stateLabels_df = deceased10_df[deceased10_df['sinceDay0'] == deceased10_df.groupby(['state'])['sinceDay0'].transform(max)]\n", + "labelChart = alt.Chart(stateLabels_df).mark_text(align='left', baseline='middle', dx=10).encode(\n", + " x='sinceDay0',\n", + " y='deceased',\n", + " text='state',\n", + " color='state')\n", + "\n", + "#now put the text labels layer on top of state labels Chart\n", + "labelChart = labelChart + alt.Chart(textLabels_df).mark_text(align='right', baseline='bottom', dx=0, size=18,opacity=0.5).encode(\n", + " x='labelX',\n", + " y='labelY',\n", + " text='labelText')\n", + "\n", + "\n", + "## Create some tooltip behavior - show Y values on mouseover\n", + "# Step 1: Selection that chooses nearest point based on value on x-axis\n", + "nearest = alt.selection(type='single', nearest=True, on='mouseover',\n", + " fields=['sinceDay0'])\n", + "\n", + "# Step 2: Transparent selectors across the chart. This is what tells us\n", + "# the x-value of the cursor\n", + "selectors = alt.Chart().mark_point().encode(\n", + " x=\"sinceDay0:Q\",\n", + " opacity=alt.value(0),\n", + ").add_selection(\n", + " nearest\n", + ")\n", + "\n", + "# Step 3: Add text, show values in column when it's the nearest point to \n", + "# mouseover, else show blank\n", + "text = lineChart.mark_text(align='center', dx=3, dy=-20).encode(\n", + " text=alt.condition(nearest, 'deceased', alt.value(' '))\n", + ")\n", + "\n", + "\n", + "#Finally, lets show the chart!\n", + "\n", + "chart = alt.layer(lineChart, ruleChart, labelChart, selectors, text, data=deceased10_df)\n", + "\n", + "display(chart)\n", + "display(html_credits)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "<div id=\"altair-viz-baae3ed02bae4c7cbfe689444af35ce6\"></div>\n", + "<script type=\"text/javascript\">\n", + " (function(spec, embedOpt){\n", + " const outputDiv = document.getElementById(\"altair-viz-baae3ed02bae4c7cbfe689444af35ce6\");\n", + " const paths = {\n", + " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", + " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", + " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", + " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", + " };\n", + "\n", + " function loadScript(lib) {\n", + " return new Promise(function(resolve, reject) {\n", + " var s = document.createElement('script');\n", + " s.src = paths[lib];\n", + " s.async = true;\n", + " s.onload = () => resolve(paths[lib]);\n", + " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", + " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", + " });\n", + " }\n", + "\n", + " function showError(err) {\n", + " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", + " throw err;\n", + " }\n", + "\n", + " function displayChart(vegaEmbed) {\n", + " vegaEmbed(outputDiv, spec, embedOpt)\n", + " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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\"tested_100k\": 1129.8315425397693, \"sinceDay0\": 9}, {\"index\": 1170, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-OH\", \"state\": \"Ohio\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 53341, \"positive\": 5148.0, \"deceased\": 193.0, \"positive_100k\": 44.32801595188602, \"deceased_100k\": 1.6618700619102569, \"tested_100k\": 459.30472006401556, \"sinceDay0\": 20}, {\"index\": 1205, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-OK\", \"state\": \"Oklahoma\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 13345, \"positive\": 1524.0, \"deceased\": 79.0, \"positive_100k\": 38.96364875651248, \"deceased_100k\": 2.0197691940711846, \"tested_100k\": 341.18759360607544, \"sinceDay0\": 15}, {\"index\": 1238, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-OR\", \"state\": \"Oregon\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 23007, \"positive\": 1181.0, \"deceased\": 33.0, \"positive_100k\": 29.3126518220382, \"deceased_100k\": 0.8190664776691453, \"tested_100k\": 571.0382561131523, \"sinceDay0\": 19}, {\"index\": 1274, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-PA\", \"state\": \"Pennsylvania\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 98538, \"positive\": 16239.0, \"deceased\": 309.0, \"positive_100k\": 126.84238386821703, \"deceased_100k\": 2.4135905299143454, \"tested_100k\": 769.6776169472486, \"sinceDay0\": 21}, {\"index\": 1308, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-RI\", \"state\": \"Rhode Island\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 12132, \"positive\": 1450.0, \"deceased\": 35.0, \"positive_100k\": 137.27186835533155, \"deceased_100k\": 3.313458891335589, \"tested_100k\": 1148.5395219909533, \"sinceDay0\": 16}, {\"index\": 1341, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-SC\", \"state\": \"South Carolina\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 24634, \"positive\": 2552.0, \"deceased\": 63.0, \"positive_100k\": 52.122628696121396, \"deceased_100k\": 1.2867263353666332, \"tested_100k\": 503.1304213558991, \"sinceDay0\": 18}, {\"index\": 1377, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-SD\", \"state\": \"South Dakota\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 6748, \"positive\": 393.0, \"deceased\": 6.0, \"positive_100k\": 45.77917199106782, \"deceased_100k\": 0.6989186563521805, \"tested_100k\": 786.0505155107522, \"sinceDay0\": 9}, {\"index\": 1410, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-TN\", \"state\": \"Tennessee\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 56618, \"positive\": 4362.0, \"deceased\": 79.0, \"positive_100k\": 66.0879151080883, \"deceased_100k\": 1.1969154730717502, \"tested_100k\": 857.8096234731184, \"sinceDay0\": 20}, {\"index\": 1445, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-TX\", \"state\": \"Texas\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 96258, \"positive\": 9353.0, \"deceased\": 177.0, \"positive_100k\": 34.049150620584264, \"deceased_100k\": 0.6443600619954469, \"tested_100k\": 350.4226601556934, \"sinceDay0\": 20}, {\"index\": 1481, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"state\": \"Utah\", \"admin2\": \"\", 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\"tested_100k\": 365.561560173079, \"sinceDay0\": 19}, {\"index\": 1583, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-WA\", \"state\": \"Washington\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 92073, \"positive\": 8682.0, \"deceased\": 394.0, \"positive_100k\": 121.08193866660083, \"deceased_100k\": 5.494849554784696, \"tested_100k\": 1284.079398623582, \"sinceDay0\": 32}, {\"index\": 1655, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-WV\", \"state\": \"West Virginia\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 12545, \"positive\": 462.0, \"deceased\": 4.0, \"positive_100k\": 25.052490933384234, \"deceased_100k\": 0.2169046834059241, \"tested_100k\": 680.2673133318294, \"sinceDay0\": 10}, {\"index\": 1619, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-WI\", \"state\": \"Wisconsin\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 32871, \"positive\": 2756.0, \"deceased\": 99.0, \"positive_100k\": 47.75323291639355, \"deceased_100k\": 1.7153737513508567, \"tested_100k\": 569.5560664712527, \"sinceDay0\": 21}, {\"index\": 1689, \"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-WY\", \"state\": \"Wyoming\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 4064, \"positive\": 221.0, \"deceased\": 0.0, \"positive_100k\": 37.70642561853041, \"deceased_100k\": 0.0, \"tested_100k\": 693.3887498357809, \"sinceDay0\": 8}], \"data-0a08c6105da7e065c75198fff0e29db2\": [{\"labelX\": 9, \"labelY\": 30000, \"labelText\": \"doubles every day\"}, {\"labelX\": 28, \"labelY\": 31000, \"labelText\": \"doubles every 3 days\"}, {\"labelX\": 32, \"labelY\": 1000, \"labelText\": \"doubles every week\"}]}}, {\"mode\": \"vega-lite\"});\n", + "</script>" + ], + "text/plain": [ + "alt.LayerChart(...)" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "<p style=\"font-size: smaller\">Data Sources: \n", + " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", + "<br>\n", + "Analysis and Visualization:\n", + " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", + "</p>" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# make dataframe for text labels on chart - hand edit these label locations\n", + "textLabels_df = pd.DataFrame(\n", + " [[9,30000,'doubles every day'],\n", + " [28,31000,'doubles every 3 days'],\n", + " [32,1000, 'doubles every week']],\n", + " columns =['labelX', 'labelY','labelText']\n", + ")\n", + "\n", + "# make dataframe with only points >=100 positives\n", + "positive100_df = data_df.loc[data_df['positive']>=100]\n", + "\n", + "## add US to that dataframe\n", + "nationpos100_df = nation_df.loc[nation_df['positive']>=100]\n", + "positive100_df= pd.concat ([positive100_df,nationpos100_df])\n", + "\n", + "# group positive100 dataframe by state and then increasing order of date\n", + "positive100_df = positive100_df.sort_values(by=['state','date'])\n", + "positive100_df = positive100_df.reset_index()\n", + "\n", + "# make a list of the states with 10 or more deaths (don't really need this)\n", + "# state_list = list(set(positive100_df['state']))\n", + "\n", + "# add a column for the number of days since the 100th case for each state\n", + "for state, df in positive100_df.groupby('state'):\n", + " positive100_df.loc[df.index,'sinceDay0'] = range(0, len(df))\n", + "positive100_df = positive100_df.astype({'sinceDay0': 'int32'})\n", + "\n", + " \n", + "# Now create plotlines for each state since 10 deaths\n", + "lineChart = alt.Chart(positive100_df, title=\"US States: total cases since 100th case\").mark_line(interpolate='basis').encode(\n", + " alt.X('sinceDay0:Q', axis=alt.Axis(title='Days since 100th case')),\n", + " alt.Y('positive:Q',\n", + " axis = alt.Axis(title='Cumulative positive cases'),\n", + " scale=alt.Scale(type='log')),\n", + " tooltip=['state', 'sinceDay0', 'deceased', 'positive'],\n", + " color = 'state'\n", + ").properties(width=800,height=400)\n", + "\n", + "## Create a layer with the lines for doubling every day and doubling every week\n", + "# make dataframe with lines to indicate doubling every day, 3 days, week \n", + "\n", + "days = {'day':[1,2,3,4,5,10,15,20, max(positive100_df.sinceDay0)+5]}\n", + "startCase = 100\n", + "logRuleDay_df = pd.DataFrame (days, columns=['day'])\n", + "logRuleDay_df['case']= startCase * pow(2,logRuleDay_df['day'])\n", + "logRuleDay_df['doubling period']='every day'\n", + "\n", + "logRule3Days_df = pd.DataFrame (days, columns=['day'])\n", + "logRule3Days_df['case']= startCase * pow(2,(logRule3Days_df['day'])/3)\n", + "logRule3Days_df['doubling period']='three days'\n", + "\n", + "logRuleWeek_df = pd.DataFrame (days, columns=['day'])\n", + "logRuleWeek_df['case']= startCase * pow(2,(logRuleWeek_df['day'])/7)\n", + "logRuleWeek_df['doubling period']='every week'\n", + "\n", + "logRules_df = pd.concat([logRuleDay_df, logRule3Days_df, logRuleWeek_df])\n", + "logRules_df = logRules_df.reset_index()\n", + "\n", + "ruleChart = alt.Chart(logRules_df).mark_line(opacity=0.2,clip=True).encode(\n", + " alt.X('day:Q',\n", + " scale=alt.Scale(domain=[1, max(positive100_df.sinceDay0)+5])),\n", + " alt.Y('case', scale=alt.Scale(domain=[100,200000], type='log'),\n", + " ),\n", + " color = 'doubling period')\n", + "\n", + "# create a layer for the state labels\n", + "# 1) make dataframe with each state's max days\n", + "# 2) make a chart layer with text of state name to right of each state's rightmost point\n", + "stateLabels_df = positive100_df[positive100_df['sinceDay0'] == positive100_df.groupby(['state'])['sinceDay0'].transform(max)]\n", + "labelChart = alt.Chart(stateLabels_df).mark_text(align='left', baseline='middle', dx=10).encode(\n", + " x='sinceDay0',\n", + " y='positive',\n", + " text='state',\n", + " color='state')\n", + "\n", + "#now put the text labels layer on top of state labels Chart\n", + "labelChart = labelChart + alt.Chart(textLabels_df).mark_text(align='right', baseline='bottom', dx=0, size=18,opacity=0.5).encode(\n", + " x='labelX',\n", + " y='labelY',\n", + " text='labelText')\n", + "\n", + "#Create some tooltip behavior\n", + "# Step 1: Selection that chooses nearest point based on value on x-axis\n", + "nearest = alt.selection(type='single', nearest=True, on='mouseover',\n", + " fields=['sinceDay0'])\n", + "\n", + "# Step 2: Transparent selectors across the chart. This is what tells us\n", + "# the x-value of the cursor\n", + "selectors = alt.Chart().mark_point().encode(\n", + " x=\"sinceDay0:Q\",\n", + " opacity=alt.value(0),\n", + ").add_selection(\n", + " nearest\n", + ")\n", + "\n", + "# Step 3: Add text, show values in Sex column when it's the nearest point to \n", + "# mouseover, else show blank\n", + "text = lineChart.mark_text(align='center', dx=3, dy=-20).encode(\n", + " text=alt.condition(nearest, 'positive', alt.value(' '))\n", + ")\n", + "\n", + "\n", + "#Finally, lets show the chart!\n", + "\n", + "chart = alt.layer(lineChart, ruleChart, labelChart, selectors, text, data=positive100_df)\n", + "#chart = alt.layer(lineChart, ruleChart, labelChart)\n", + "chart.properties (width=400,height=800)\n", + "display(chart)\n", + "display(html_credits)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Daily Cumulative Totals\n", + "\n", + "Cumulative reported totals of positive cases and deaths. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "<div id=\"altair-viz-1acb1f3562e24ba5977e68c65ab9a6e8\"></div>\n", + "<script type=\"text/javascript\">\n", + " (function(spec, embedOpt){\n", + " const outputDiv = document.getElementById(\"altair-viz-1acb1f3562e24ba5977e68c65ab9a6e8\");\n", + " const paths = {\n", + " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", + " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", + " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", + " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", + " };\n", + "\n", + " function loadScript(lib) {\n", + " return new Promise(function(resolve, reject) {\n", + " var s = document.createElement('script');\n", + " s.src = paths[lib];\n", + " s.async = true;\n", + " s.onload = () => resolve(paths[lib]);\n", + " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", + " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", + " });\n", + " }\n", + "\n", + " function showError(err) {\n", + " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", + " throw err;\n", + " }\n", + "\n", + " function displayChart(vegaEmbed) {\n", + " vegaEmbed(outputDiv, spec, embedOpt)\n", + " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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\"width\": 400}, {\"mark\": {\"type\": \"bar\", \"size\": 7}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"positive_diff\", \"title\": \"Daily cases\"}}, \"height\": 200, \"width\": 400}]}, {\"hconcat\": [{\"mark\": {\"type\": \"bar\", \"size\": 7}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"deceased\", \"title\": \"Cumulative deaths\"}}, \"height\": 200, \"width\": 400}, {\"mark\": {\"type\": \"bar\", \"size\": 7}, \"encoding\": {\"x\": {\"type\": \"temporal\", \"axis\": {\"title\": \"\"}, \"field\": \"date\"}, \"y\": {\"type\": \"quantitative\", \"field\": \"deceased_diff\", \"title\": \"Daily deaths\"}}, \"height\": 200, \"width\": 400}]}], \"data\": {\"name\": \"data-74f796fa34767ca8c52c1a1d6dbf074c\"}, \"title\": \"Cumulative Covid-19 cases and deaths in the U.S.\", \"$schema\": 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+ ], + "text/plain": [ + "alt.VConcatChart(...)" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "<p style=\"font-size: smaller\">Data Sources: \n", + " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", + "<br>\n", + "Analysis and Visualization:\n", + " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", + "</p>" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "base = alt.Chart(\n", + " daily_totals\n", + ").mark_bar(size=7).encode(\n", + " alt.X('date', axis=alt.Axis(title='')\n", + " )\n", + ").properties(\n", + " height=200,\n", + " width=400\n", + ")\n", + "\n", + "cumulative = base.encode(alt.Y('positive', title = 'Cumulative cases'))\n", + "cumulative_deaths = base.encode(alt.Y('deceased', title = 'Cumulative deaths'))\n", + "rates = base.encode(alt.Y('positive_diff', title='Daily cases'))\n", + "rates_deaths = base.encode(alt.Y('deceased_diff', title='Daily deaths'))\n", + "chart = alt.vconcat(\n", + " cumulative | rates, cumulative_deaths | rates_deaths,\n", + " title='Cumulative Covid-19 cases and deaths in the U.S.'\n", + ").configure_title(\n", + " anchor='middle'\n", + ")\n", + "display(chart)\n", + "display(html_credits)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Total tests and positives per 100k population" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Most recent test date 2020-04-08 00:00:00\n", + "50 states/territories have data on this date.\n" + ] + } + ], + "source": [ + "most_recent_test_date = data_df['date'].max()\n", + "most_recent_df = data_df[data_df['date'] == most_recent_test_date]\n", + "print(\"Most recent test date\", most_recent_test_date)\n", + "print(len(most_recent_df), \"states/territories have data on this date.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "<div id=\"altair-viz-1d961b2a7acd439cbaa18a94a3cc700c\"></div>\n", + "<script type=\"text/javascript\">\n", + " (function(spec, embedOpt){\n", + " const outputDiv = document.getElementById(\"altair-viz-1d961b2a7acd439cbaa18a94a3cc700c\");\n", + " const paths = {\n", + " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", + " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", + " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", + " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", + " };\n", + "\n", + " function loadScript(lib) {\n", + " return new Promise(function(resolve, reject) {\n", + " var s = document.createElement('script');\n", + " s.src = paths[lib];\n", + " 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\"country_label\": \"United States of America\", \"region_iso\": \"US-NM\", \"state\": \"New Mexico\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 22245, \"positive\": 794.0, \"deceased\": 13.0, \"positive_100k\": 38.07954404302125, \"deceased_100k\": 0.6234686052383832, \"tested_100k\": 1066.8507018098335}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-HI\", \"state\": \"Hawaii\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 15149, \"positive\": 410.0, \"deceased\": 5.0, \"positive_100k\": 28.63922470126145, \"deceased_100k\": 0.3492588378202616, \"tested_100k\": 1058.1844268278287}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-AK\", \"state\": \"Alaska\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 7068, \"positive\": 226.0, \"deceased\": 7.0, \"positive_100k\": 30.605390882301958, 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Hampshire\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 9177, \"positive\": 788.0, \"deceased\": 18.0, \"positive_100k\": 59.221047821747646, \"deceased_100k\": 1.3527650517658092, \"tested_100k\": 689.6847155586019}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-MS\", \"state\": \"Mississippi\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 20635, \"positive\": 2003.0, \"deceased\": 67.0, \"positive_100k\": 66.93773721039737, \"deceased_100k\": 2.239055613128619, \"tested_100k\": 689.5957101031202}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-WV\", \"state\": \"West Virginia\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 12545, \"positive\": 462.0, \"deceased\": 4.0, \"positive_100k\": 25.052490933384234, \"deceased_100k\": 0.2169046834059241, \"tested_100k\": 680.2673133318294}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-MD\", \"state\": \"Maryland\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 38462, \"positive\": 5529.0, \"deceased\": 124.0, \"positive_100k\": 92.0517960755534, \"deceased_100k\": 2.0644642274133878, \"tested_100k\": 640.3501864094656}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-IL\", \"state\": \"Illinois\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 75066, \"positive\": 15078.0, \"deceased\": 462.0, \"positive_100k\": 117.24732396863297, \"deceased_100k\": 3.592536389011038, \"tested_100k\": 583.717178739183}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-OR\", \"state\": \"Oregon\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 23007, \"positive\": 1181.0, \"deceased\": 33.0, \"positive_100k\": 29.3126518220382, \"deceased_100k\": 0.8190664776691453, \"tested_100k\": 571.0382561131523}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-WI\", \"state\": \"Wisconsin\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 32871, \"positive\": 2756.0, \"deceased\": 99.0, \"positive_100k\": 47.75323291639355, \"deceased_100k\": 1.7153737513508567, \"tested_100k\": 569.5560664712527}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-MO\", \"state\": \"Missouri\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 34110, \"positive\": 3327.0, \"deceased\": 58.0, \"positive_100k\": 54.687366445791284, \"deceased_100k\": 0.953371582162878, \"tested_100k\": 560.6811149582029}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-MN\", \"state\": \"Minnesota\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 30753, \"positive\": 1154.0, \"deceased\": 39.0, \"positive_100k\": 21.02159103205082, \"deceased_100k\": 0.7104350522096898, \"tested_100k\": 560.2053630924254}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-MI\", \"state\": \"Michigan\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 51708, \"positive\": 20346.0, \"deceased\": 959.0, \"positive_100k\": 205.04756023032726, \"deceased_100k\": 9.664828971831508, \"tested_100k\": 521.114678285155}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-CO\", \"state\": \"Colorado\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 28094, \"positive\": 5429.0, \"deceased\": 179.0, \"positive_100k\": 99.49466460090159, \"deceased_100k\": 3.2804466685506326, \"tested_100k\": 514.8651883031367}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-AZ\", \"state\": \"Arizona\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 34564, \"positive\": 2726.0, \"deceased\": 80.0, \"positive_100k\": 39.92346294301533, \"deceased_100k\": 1.1716350093328052, \"tested_100k\": 506.2049057822385}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-SC\", \"state\": \"South Carolina\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 24634, \"positive\": 2552.0, \"deceased\": 63.0, \"positive_100k\": 52.122628696121396, \"deceased_100k\": 1.2867263353666332, \"tested_100k\": 503.1304213558991}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-ME\", \"state\": \"Maine\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 6625, 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States of America\", \"region_iso\": \"US-IN\", \"state\": \"Indiana\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 30869, \"positive\": 5943.0, \"deceased\": 203.0, \"positive_100k\": 89.77775360742513, \"deceased_100k\": 3.0666134918908465, \"tested_100k\": 466.321634882653}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-OH\", \"state\": \"Ohio\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 53341, \"positive\": 5148.0, \"deceased\": 193.0, \"positive_100k\": 44.32801595188602, \"deceased_100k\": 1.6618700619102569, \"tested_100k\": 459.30472006401556}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-IA\", \"state\": \"Iowa\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 13966, \"positive\": 1145.0, \"deceased\": 27.0, \"positive_100k\": 37.58590184006788, \"deceased_100k\": 0.8863051088924305, \"tested_100k\": 458.4495241033957}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-NC\", \"state\": \"North Carolina\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 42987, \"positive\": 3426.0, \"deceased\": 53.0, \"positive_100k\": 34.113985320033194, \"deceased_100k\": 0.5277411622772211, \"tested_100k\": 428.03791212850757}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-NE\", \"state\": \"Nebraska\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 7961, \"positive\": 519.0, \"deceased\": 12.0, \"positive_100k\": 27.37067487962704, \"deceased_100k\": 0.6328479740954229, \"tested_100k\": 419.8418934811385}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-AL\", \"state\": \"Alabama\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 19122, \"positive\": 2369.0, \"deceased\": 66.0, \"positive_100k\": 48.75509855053912, \"deceased_100k\": 1.3583100482632258, \"tested_100k\": 393.53946580135454}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-GA\", \"state\": \"Georgia\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 38787, \"positive\": 9901.0, \"deceased\": 362.0, \"positive_100k\": 96.92741750743525, \"deceased_100k\": 3.543856695050152, \"tested_100k\": 379.7115183174317}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-CA\", \"state\": \"California\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 144264, \"positive\": 16957.0, \"deceased\": 442.0, \"positive_100k\": 43.31863287753695, \"deceased_100k\": 1.1291405161214443, \"tested_100k\": 368.5392023025883}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-VA\", \"state\": \"Virginia\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 30645, \"positive\": 3645.0, \"deceased\": 75.0, \"positive_100k\": 43.48089041706226, \"deceased_100k\": 0.8946685271000464, \"tested_100k\": 365.561560173079}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-TX\", \"state\": \"Texas\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 96258, \"positive\": 9353.0, \"deceased\": 177.0, \"positive_100k\": 34.049150620584264, \"deceased_100k\": 0.6443600619954469, \"tested_100k\": 350.4226601556934}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-OK\", \"state\": \"Oklahoma\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 13345, \"positive\": 1524.0, \"deceased\": 79.0, \"positive_100k\": 38.96364875651248, \"deceased_100k\": 2.0197691940711846, \"tested_100k\": 341.18759360607544}, {\"date\": \"2020-04-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-KS\", \"state\": \"Kansas\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 9514, \"positive\": 900.0, \"deceased\": 27.0, \"positive_100k\": 30.9104041329271, \"deceased_100k\": 0.927312123987813, \"tested_100k\": 326.75731657852054}]}}, {\"mode\": \"vega-lite\"});\n", + "</script>" + ], + "text/plain": [ + "alt.LayerChart(...)" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "<p style=\"font-size: smaller\">Data Sources: \n", + " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", + "<br>\n", + "Analysis and Visualization:\n", + " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", + "</p>" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "viz_df = most_recent_df.sort_values('tested_100k', ascending=False)\n", + "chart = alt.Chart(viz_df, title=\"Cases (orange points) and tests(blue bars) per 100k\").encode(alt.X('state', sort=None))\n", + "tests = chart.mark_bar().encode(alt.Y('tested_100k', axis=alt.Axis(title='COVID-19 Tests/100k, Positive Cases/100k')))\n", + "positives = chart.mark_point(color='orange', filled=True, size=100, opacity=1).encode(alt.Y('positive_100k'))\n", + "display(alt.layer(tests, positives))\n", + "display(html_credits)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Counts and rates by state\n", + "\n", + "Taking a look at the three states with the highest per-capita incidence of covid-19. The red and yellow curves represent the total tests and total positive tests respectively. " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "<div id=\"altair-viz-93534fdc5b0749149314eef9b2863540\"></div>\n", + "<script type=\"text/javascript\">\n", + " (function(spec, embedOpt){\n", + " const outputDiv = document.getElementById(\"altair-viz-93534fdc5b0749149314eef9b2863540\");\n", + " const paths = {\n", + " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", + " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", + " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", + " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", + " };\n", + "\n", + " function loadScript(lib) {\n", + " return new Promise(function(resolve, reject) {\n", + " var s = document.createElement('script');\n", + " s.src = paths[lib];\n", + " s.async = true;\n", + " s.onload = () => resolve(paths[lib]);\n", + " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", + " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", + " });\n", + " }\n", + "\n", + " function showError(err) {\n", + " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", + " throw err;\n", + " }\n", + "\n", + " function displayChart(vegaEmbed) {\n", + " vegaEmbed(outputDiv, spec, embedOpt)\n", + " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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\"admin2_label\": \"\", \"tested\": 36116, \"positive\": 1846.0, \"deceased\": 13.0, \"positive_100k\": 66.79004372468464, \"deceased_100k\": 0.4703524205963707, \"tested_100k\": 1306.7113863275788, \"positive_diff\": 108.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 3.90754318649293, \"deceased_100k_diff\": 0.0, \"total_10\": 3611.6}, {\"state\": \"Utah\", \"date\": \"2020-04-07T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 34647, \"positive\": 1738.0, \"deceased\": 13.0, \"positive_100k\": 62.88250053819171, \"deceased_100k\": 0.4703524205963707, \"tested_100k\": 1253.5615628001888, \"positive_diff\": 63.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 2.2794001921208604, \"deceased_100k_diff\": 0.0, \"total_10\": 3464.7}, {\"state\": \"Utah\", \"date\": \"2020-04-06T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 33394, \"positive\": 1675.0, \"deceased\": 13.0, \"positive_100k\": 60.603100346070846, \"deceased_100k\": 0.4703524205963707, \"tested_100k\": 1208.2268256457849, \"positive_diff\": 70.0, \"deceased_diff\": 5.0, \"positive_100k_diff\": 2.5326668801343075, \"deceased_100k_diff\": 0.1809047771524503, \"total_10\": 3339.4}, {\"state\": \"Utah\", \"date\": \"2020-04-05T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 30892, \"positive\": 1605.0, \"deceased\": 8.0, \"positive_100k\": 58.07043346593654, \"deceased_100k\": 0.28944764344392043, \"tested_100k\": 1117.7020751586986, \"positive_diff\": 177.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 6.404029111196749, \"deceased_100k_diff\": 0.0, \"total_10\": 3089.2}, {\"state\": \"Utah\", \"date\": \"2020-04-04T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 28043, \"positive\": 1428.0, \"deceased\": 8.0, \"positive_100k\": 51.66640435473979, \"deceased_100k\": 0.28944764344392043, \"tested_100k\": 1014.6225331372325, \"positive_diff\": 182.0, \"deceased_diff\": 1.0, \"positive_100k_diff\": 6.584933888349184, \"deceased_100k_diff\": 0.03618095543049005, \"total_10\": 2804.3}, {\"state\": \"Utah\", \"date\": \"2020-04-03T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 24248, \"positive\": 1246.0, \"deceased\": 7.0, \"positive_100k\": 45.081470466390606, \"deceased_100k\": 0.2532666880134304, \"tested_100k\": 877.3158072785229, \"positive_diff\": 172.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 6.223124334044286, \"deceased_100k_diff\": 0.0, \"total_10\": 2424.8}, {\"state\": \"Utah\", \"date\": \"2020-04-02T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 21065, \"positive\": 1074.0, \"deceased\": 7.0, \"positive_100k\": 38.85834613234632, \"deceased_100k\": 0.2532666880134304, \"tested_100k\": 762.151826143273, \"positive_diff\": 62.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 2.2432192366903863, \"deceased_100k_diff\": 0.0, \"total_10\": 2106.5}, {\"state\": \"Utah\", \"date\": \"2020-04-01T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 21167, \"positive\": 1012.0, \"deceased\": 7.0, \"positive_100k\": 36.61512689565593, \"deceased_100k\": 0.2532666880134304, \"tested_100k\": 765.8422835971829, \"positive_diff\": 125.0, \"deceased_diff\": 2.0, \"positive_100k_diff\": 4.522619428811254, \"deceased_100k_diff\": 0.07236191086098012, \"total_10\": 2116.7}, {\"state\": \"Utah\", \"date\": \"2020-03-31T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 18513, \"positive\": 887.0, \"deceased\": 5.0, \"positive_100k\": 32.09250746684468, \"deceased_100k\": 0.18090477715245026, \"tested_100k\": 669.8180278846623, \"positive_diff\": 81.0, \"deceased_diff\": 1.0, \"positive_100k_diff\": 2.9306573898696975, \"deceased_100k_diff\": 0.03618095543049005, \"total_10\": 1851.3}, {\"state\": \"Utah\", \"date\": \"2020-03-30T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 16003, \"positive\": 806.0, \"deceased\": 4.0, \"positive_100k\": 29.161850076974982, \"deceased_100k\": 0.14472382172196022, \"tested_100k\": 579.0038297541323, \"positive_diff\": 87.0, \"deceased_diff\": 2.0, \"positive_100k_diff\": 3.1477431224526313, \"deceased_100k_diff\": 0.07236191086098011, \"total_10\": 1600.3}, {\"state\": \"Utah\", \"date\": \"2020-03-29T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 13993, \"positive\": 719.0, \"deceased\": 2.0, \"positive_100k\": 26.01410695452235, \"deceased_100k\": 0.07236191086098011, \"tested_100k\": 506.2801093388473, \"positive_diff\": 117.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 4.23317178536734, \"deceased_100k_diff\": 0.0, \"total_10\": 1399.3}, {\"state\": \"Utah\", \"date\": \"2020-03-28T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 11312, \"positive\": 602.0, \"deceased\": 2.0, \"positive_100k\": 21.78093516915501, \"deceased_100k\": 0.07236191086098011, \"tested_100k\": 409.2789678297035, \"positive_diff\": 122.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 4.414076562519785, \"deceased_100k_diff\": 0.0, \"total_10\": 1131.2}, {\"state\": \"Utah\", \"date\": \"2020-03-27T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 9244, \"positive\": 480.0, \"deceased\": 2.0, \"positive_100k\": 17.366858606635226, \"deceased_100k\": 0.07236191086098011, \"tested_100k\": 334.4567519994501, \"positive_diff\": 78.0, \"deceased_diff\": 1.0, \"positive_100k_diff\": 2.8221145235782252, \"deceased_100k_diff\": 0.036180955430490054, \"total_10\": 924.4}, {\"state\": \"Utah\", \"date\": \"2020-03-26T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 7710, \"positive\": 402.0, \"deceased\": 1.0, \"positive_100k\": 14.544744083057001, \"deceased_100k\": 0.036180955430490054, \"tested_100k\": 278.9551663690783, \"positive_diff\": 56.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 2.0261335041074435, \"deceased_100k_diff\": 0.0, \"total_10\": 771.0}, {\"state\": \"Utah\", \"date\": \"2020-03-25T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 6837, \"positive\": 346.0, \"deceased\": 1.0, \"positive_100k\": 12.518610578949557, \"deceased_100k\": 0.036180955430490054, \"tested_100k\": 247.36919227826047, \"positive_diff\": 47.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 1.700504905233032, \"deceased_100k_diff\": 0.0, \"total_10\": 683.7}, {\"state\": \"Utah\", \"date\": \"2020-03-24T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 5823, \"positive\": 299.0, \"deceased\": 1.0, \"positive_100k\": 10.818105673716525, \"deceased_100k\": 0.036180955430490054, \"tested_100k\": 210.6817034717436, \"positive_diff\": 42.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 1.5196001280805813, \"deceased_100k_diff\": 0.0, \"total_10\": 582.3}, {\"state\": \"Utah\", \"date\": \"2020-03-23T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 5047, \"positive\": 257.0, \"deceased\": 1.0, \"positive_100k\": 9.298505545635944, \"deceased_100k\": 0.036180955430490054, \"tested_100k\": 182.6052820576833, \"positive_diff\": 76.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 2.749752612717244, \"deceased_100k_diff\": 0.0, \"total_10\": 504.7}, {\"state\": \"Utah\", \"date\": \"2020-03-22T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 3689, \"positive\": 181.0, \"deceased\": 1.0, \"positive_100k\": 6.5487529329187, \"deceased_100k\": 0.036180955430490054, \"tested_100k\": 133.47154458307782, \"positive_diff\": 45.0, \"deceased_diff\": 1.0, \"positive_100k_diff\": 1.6281429943720527, \"deceased_100k_diff\": 0.036180955430490054, \"total_10\": 368.9}, {\"state\": \"Utah\", \"date\": \"2020-03-21T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 2560, \"positive\": 136.0, \"deceased\": 0.0, \"positive_100k\": 4.920609938546647, \"deceased_100k\": 0.0, \"tested_100k\": 92.62324590205453, \"positive_diff\": 24.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 0.8683429303317611, \"deceased_100k_diff\": 0.0, \"total_10\": 256.0}, {\"state\": \"Utah\", \"date\": \"2020-03-20T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 2147, \"positive\": 112.0, \"deceased\": 0.0, \"positive_100k\": 4.052267008214886, \"deceased_100k\": 0.0, \"tested_100k\": 77.68051130926214, \"positive_diff\": 34.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 1.2301524846366618, \"deceased_100k_diff\": 0.0, \"total_10\": 214.7}, {\"state\": \"Utah\", \"date\": \"2020-03-19T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 1526, \"positive\": 78.0, \"deceased\": 0.0, \"positive_100k\": 2.8221145235782243, \"deceased_100k\": 0.0, \"tested_100k\": 55.21213798692782, \"positive_diff\": 15.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 0.542714331457351, \"deceased_100k_diff\": 0.0, \"total_10\": 152.6}, {\"state\": \"Utah\", \"date\": \"2020-03-18T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 194, \"positive\": 63.0, \"deceased\": 0.0, \"positive_100k\": 2.2794001921208733, \"deceased_100k\": 0.0, \"tested_100k\": 7.019105353515069, \"positive_diff\": 12.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 0.43417146516588057, \"deceased_100k_diff\": 0.0, \"total_10\": 19.4}, {\"state\": \"Utah\", \"date\": \"2020-03-17T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 182, \"positive\": 51.0, \"deceased\": 0.0, \"positive_100k\": 1.8452287269549927, \"deceased_100k\": 0.0, \"tested_100k\": 6.584933888349189, \"positive_diff\": 12.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 0.43417146516588057, \"deceased_100k_diff\": 0.0, \"total_10\": 18.2}, {\"state\": \"Utah\", \"date\": \"2020-03-16T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 170, \"positive\": 39.0, \"deceased\": 0.0, \"positive_100k\": 1.4110572617891122, \"deceased_100k\": 0.0, \"tested_100k\": 6.150762423183308, \"positive_diff\": 11.0, \"deceased_diff\": 0.0, \"positive_100k_diff\": 0.39799050973539063, \"deceased_100k_diff\": 0.0, \"total_10\": 17.0}, {\"state\": \"Utah\", \"date\": \"2020-03-15T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 159, \"positive\": 28.0, \"deceased\": 0.0, \"positive_100k\": 1.0130667520537215, \"deceased_100k\": 0.0, \"tested_100k\": 5.752771913447918, \"positive_diff\": 22.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.7959810194707813, \"deceased_100k_diff\": null, \"total_10\": 15.9}, {\"state\": \"Utah\", \"date\": \"2020-03-14T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 137, \"positive\": 6.0, \"deceased\": null, \"positive_100k\": 0.2170857325829403, \"deceased_100k\": null, \"tested_100k\": 4.9567908939771375, \"positive_diff\": 0.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.0, \"deceased_100k_diff\": null, \"total_10\": 13.7}, {\"state\": \"Utah\", \"date\": \"2020-03-13T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 137, \"positive\": 6.0, \"deceased\": null, \"positive_100k\": 0.2170857325829403, \"deceased_100k\": null, \"tested_100k\": 4.9567908939771375, \"positive_diff\": 2.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.0723619108609801, \"deceased_100k_diff\": null, \"total_10\": 13.7}, {\"state\": \"Utah\", \"date\": \"2020-03-12T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 135, \"positive\": 4.0, \"deceased\": null, \"positive_100k\": 0.14472382172196022, \"deceased_100k\": null, \"tested_100k\": 4.884428983116157, \"positive_diff\": 2.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.07236191086098011, \"deceased_100k_diff\": null, \"total_10\": 13.5}, {\"state\": \"Utah\", \"date\": \"2020-03-11T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 2, \"positive\": 2.0, \"deceased\": null, \"positive_100k\": 0.07236191086098011, \"deceased_100k\": null, \"tested_100k\": 0.07236191086098011, \"positive_diff\": 0.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.0, \"deceased_100k_diff\": null, \"total_10\": 0.2}, {\"state\": \"Utah\", \"date\": \"2020-03-10T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 2, \"positive\": 2.0, \"deceased\": null, \"positive_100k\": 0.07236191086098011, \"deceased_100k\": null, \"tested_100k\": 0.07236191086098011, \"positive_diff\": 1.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.036180955430490054, \"deceased_100k_diff\": null, \"total_10\": 0.2}, {\"state\": \"Utah\", \"date\": \"2020-03-09T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 1, \"positive\": 1.0, \"deceased\": null, \"positive_100k\": 0.036180955430490054, \"deceased_100k\": null, \"tested_100k\": 0.036180955430490054, \"positive_diff\": 0.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.0, \"deceased_100k_diff\": null, \"total_10\": 0.1}, {\"state\": \"Utah\", \"date\": \"2020-03-08T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 1, \"positive\": 1.0, \"deceased\": null, \"positive_100k\": 0.036180955430490054, \"deceased_100k\": null, \"tested_100k\": 0.036180955430490054, \"positive_diff\": 0.0, \"deceased_diff\": null, \"positive_100k_diff\": 0.0, \"deceased_100k_diff\": null, \"total_10\": 0.1}, {\"state\": \"Utah\", \"date\": \"2020-03-07T00:00:00\", \"country\": \"USA\", \"country_label\": \"United States of America\", \"region_iso\": \"US-UT\", \"admin2\": \"\", \"admin2_label\": \"\", \"tested\": 1, \"positive\": 1.0, \"deceased\": null, \"positive_100k\": 0.036180955430490054, \"deceased_100k\": null, \"tested_100k\": 0.036180955430490054, \"positive_diff\": null, \"deceased_diff\": null, \"positive_100k_diff\": null, \"deceased_100k_diff\": null, \"total_10\": 0.1}]}}, {\"mode\": \"vega-lite\"});\n", + "</script>" + ], + "text/plain": [ + "alt.HConcatChart(...)" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "<p style=\"font-size: smaller\">Data Sources: \n", + " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", + "<br>\n", + "Analysis and Visualization:\n", + " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", + "</p>" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# produce the charts for a few states\n", + "\n", + "charts=[]\n", + "for state in most_recent_df.sort_values('tested_100k', ascending=False)['state'].to_list()[:3]: \n", + " state_df = tdf_diff[tdf_diff['state'] == state].copy()\n", + "\n", + " base = alt.Chart(state_df, title=state).encode(alt.X('date', axis=alt.Axis(title='Date'))).properties(width=250, height=150)\n", + " dailies = base.mark_bar(size=6).encode(alt.Y('positive_diff', axis=alt.Axis(title='Daily positive')))\n", + "\n", + " totals = base.mark_line(color='red').encode(alt.Y('total_10', axis=alt.Axis(title='Total/10'))) \n", + " positives = totals.mark_line(color='orange').encode(alt.Y('positive', axis=alt.Axis(title='Positive')))\n", + " cumulative = totals + positives\n", + "\n", + " ratio = base.mark_line(color='red').encode(alt.Y('ratio', axis=alt.Axis(title='Positive/Total'), scale=alt.Scale(domain=(0,1))))\n", + " \n", + " charts.append(alt.layer(dailies, cumulative).resolve_scale(y='independent'))\n", + "\n", + "display(alt.hconcat(*charts))\n", + "display(html_credits)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": true, + "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": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/runs/covidtracking-dashboard.ipynb b/runs/covidtracking-dashboard.ipynb deleted file mode 100644 index 94eeafe52a06d75e2a16c599746e6671794950e8..0000000000000000000000000000000000000000 --- a/runs/covidtracking-dashboard.ipynb +++ /dev/null @@ -1,1046 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "papermill": { - "duration": 0.67093, - "end_time": "2020-04-09T07:26:20.928825", - "exception": false, - "start_time": "2020-04-09T07:26:20.257895", - "status": "completed" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "from pathlib import Path\n", - "\n", - "import pandas as pd\n", - "import altair as alt\n", - "from IPython.display import display, HTML" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "papermill": { - "duration": 0.022891, - "end_time": "2020-04-09T07:26:20.964915", - "exception": false, - "start_time": "2020-04-09T07:26:20.942024", - "status": "completed" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "html_credits=HTML('''\n", - "<p style=\"font-size: smaller\">Data Sources: \n", - " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", - "<br>\n", - "Analysis and Visualization:\n", - " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", - "</p>''')" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "papermill": { - "duration": 0.022575, - "end_time": "2020-04-09T07:26:21.000160", - "exception": false, - "start_time": "2020-04-09T07:26:20.977585", - "status": "completed" - }, - "tags": [ - "parameters" - ] - }, - "outputs": [], - "source": [ - "data_path = '../data/covidtracking'" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "papermill": { - "duration": 0.023711, - "end_time": "2020-04-09T07:26:21.037362", - "exception": false, - "start_time": "2020-04-09T07:26:21.013651", - "status": "completed" - }, - "tags": [ - "injected-parameters" - ] - }, - "outputs": [], - "source": [ - "# Parameters\n", - "data_path = \"/tmp/yrqgj0hh/data/covidtracking\"\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "papermill": { - "duration": 0.21598, - "end_time": "2020-04-09T07:26:21.267244", - "exception": false, - "start_time": "2020-04-09T07:26:21.051264", - "status": "completed" - }, - "tags": [] - }, - "outputs": [], - "source": [ - "# Read population data\n", - "pop_df = pd.read_csv(Path(data_path) / '../geodata/us_pop_fung_2019.csv').set_index('ST')\n", - "\n", - "# Read state-level data\n", - "data_df = pd.read_json(Path(data_path) / 'states-daily.json')\n", - "data_df['date'] = pd.to_datetime(data_df['date'], format=\"%Y%m%d\")\n", - "data_df['ratio'] = data_df['positive']/data_df['total']\n", - "\n", - "# Compute daily differences\n", - "tdf = data_df.sort_values(['state', 'date'], ascending=[True, False]).set_index(['state', 'date'])\n", - "diffs_df = tdf[['positive', 'negative', 'death']].groupby(level='state').diff(periods=-1).dropna(how='all')\n", - "tdf_diff=tdf.join(diffs_df, rsuffix='_diff').reset_index()\n", - "\n", - "# incidence rates\n", - "tdf_diff = tdf_diff.set_index('state')\n", - "tdf_diff['positive_diff_100k'] = (tdf_diff['positive_diff'] / pop_df['Population']) * 100000\n", - "tdf_diff['death_diff_100k'] = (tdf_diff['death_diff'] / pop_df['Population']) * 100000\n", - "tdf_diff = tdf_diff.reset_index()\n", - "\n", - "# \"Normalizing\" the totals\n", - "tdf_diff['total_10'] = tdf_diff['total']/10.\n", - "\n", - "# Daily totals\n", - "daily_totals = tdf_diff.groupby('date').sum()\n", - "daily_totals.reset_index(level=0, inplace=True)\n", - "\n", - "# National daily totals\n", - "nation_df = data_df.groupby('date').sum()\n", - "nation_df['state']='All US'\n", - "nation_df = nation_df.reset_index()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "papermill": { - "duration": 0.012305, - "end_time": "2020-04-09T07:26:21.295195", - "exception": false, - "start_time": "2020-04-09T07:26:21.282890", - "status": "completed" - }, - "tags": [] - }, - "source": [ - "# Covid-19 Cases in U.S.\n", - "\n", - "The case data from the U.S. is obtained from https://covidtracking.com, a public crowd-sourced covid-19 dataset. " - ] - }, - { - "cell_type": "markdown", - "metadata": { - "papermill": { - "duration": 0.010649, - "end_time": "2020-04-09T07:26:21.317049", - "exception": false, - "start_time": "2020-04-09T07:26:21.306400", - "status": "completed" - }, - "tags": [] - }, - "source": [ - "### Growth trends" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "papermill": { - "duration": 0.629229, - "end_time": "2020-04-09T07:26:21.958464", - "exception": false, - "start_time": "2020-04-09T07:26:21.329235", - "status": "completed" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "<div id=\"altair-viz-30bdae5f847d4b1f90a8c74ba7f61bb3\"></div>\n", - "<script type=\"text/javascript\">\n", - " (function(spec, embedOpt){\n", - " const outputDiv = document.getElementById(\"altair-viz-30bdae5f847d4b1f90a8c74ba7f61bb3\");\n", - " const paths = {\n", - " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", - " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", - " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", - " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", - " };\n", - "\n", - " function loadScript(lib) {\n", - " return new Promise(function(resolve, reject) {\n", - " var s = document.createElement('script');\n", - " s.src = paths[lib];\n", - " s.async = true;\n", - " s.onload = () => resolve(paths[lib]);\n", - " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", - " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", - " });\n", - " }\n", - "\n", - " function showError(err) {\n", - " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", - " throw err;\n", - " }\n", - "\n", - " function displayChart(vegaEmbed) {\n", - " vegaEmbed(outputDiv, spec, embedOpt)\n", - " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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\"onVentilatorCurrently\": 4073.0, \"onVentilatorCumulative\": 216.0, \"recovered\": 19248.0, \"hash\": null, \"dateChecked\": null, \"death\": 14495.0, \"hospitalized\": 47159.0, \"total\": 2212999, \"totalTestResults\": 2195771, \"posNeg\": 2195771, \"fips\": 1822, \"deathIncrease\": 1874.0, \"hospitalizedIncrease\": 1579.0, \"negativeIncrease\": 110739.0, \"positiveIncrease\": 30570.0, \"totalTestResultsIncrease\": 141309.0, \"ratio\": 6.911529018632508, \"sinceDay0\": 35}], \"data-d7d4401f932869a4aec747d1ffc1bfec\": [{\"labelX\": 10, \"labelY\": 6000, \"labelText\": \"doubles every day\"}, {\"labelX\": 28, \"labelY\": 7000, \"labelText\": \"doubles every 3 days\"}, {\"labelX\": 34, \"labelY\": 100, \"labelText\": \"doubles every week\"}]}}, {\"mode\": \"vega-lite\"});\n", - "</script>" - ], - "text/plain": [ - "alt.LayerChart(...)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "<p style=\"font-size: smaller\">Data Sources: \n", - " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", - "<br>\n", - "Analysis and Visualization:\n", - " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", - "</p>" - ], - "text/plain": [ - "<IPython.core.display.HTML object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# make dataframe for text labels on chart - hand edit these label locations\n", - "textLabels_df = pd.DataFrame(\n", - " [[10,6000,'doubles every day'],\n", - " [28,7000,'doubles every 3 days'],\n", - " [34,100, 'doubles every week']],\n", - " columns =['labelX', 'labelY','labelText']\n", - ")\n", - "\n", - "# make dataframe of states with points >=10 deaths\n", - "death10_df = data_df.loc[data_df['death']>=10]\n", - "\n", - "# group death10 dataframe by state and then increasing order of date\n", - "death10_df = death10_df.sort_values(by=['state','date'])\n", - "\n", - "# add US to that dataframe\n", - "nationdeath10_df = nation_df.loc[nation_df['death']>=10]\n", - "death10_df= pd.concat ([death10_df,nationdeath10_df])\n", - "\n", - "death10_df = death10_df.reset_index()\n", - "\n", - "# make a list of the states with 10 or more deaths\n", - "state_list = list(set(death10_df['state']))\n", - "\n", - "# add a column for the number of days since the 10th death for each state\n", - "for state, df in death10_df.groupby('state'):\n", - " death10_df.loc[df.index,'sinceDay0'] = range(0, len(df))\n", - "death10_df = death10_df.astype({'sinceDay0': 'int32'})\n", - "\n", - "#Now create plotlines for each state since 10 deaths\n", - "lineChart = alt.Chart(death10_df,title='US States: Cumulative Deaths Since 10th Death').mark_line(interpolate='basis').encode(\n", - " alt.X('sinceDay0:Q', axis=alt.Axis(title='Days Since 10th Death')),\n", - " alt.Y('death:Q',\n", - " axis = alt.Axis(title='Cumulative Deaths'),\n", - " scale=alt.Scale(type='log')),\n", - " tooltip=['state', 'sinceDay0', 'death', 'positive'],\n", - " color = 'state'\n", - ").properties(width=800,height=400)\n", - "\n", - "## Create a layer with the lines for doubling every day and doubling every week\n", - "\n", - "# Compute theoretical trends of doubling every day, 3 days, week\n", - "days = {'day':[1,2,3,4,5,10,15,20, max(death10_df.sinceDay0)+5]}\n", - "startCase = 10\n", - "logRuleDay_df = pd.DataFrame(days, columns=['day'])\n", - "logRuleDay_df['case']= startCase * pow(2,logRuleDay_df['day'])\n", - "logRuleDay_df['doubling period']='every day'\n", - "\n", - "logRule3Days_df = pd.DataFrame(days, columns=['day'])\n", - "logRule3Days_df['case']= startCase * pow(2,(logRule3Days_df['day'])/3)\n", - "logRule3Days_df['doubling period']='three days'\n", - "\n", - "logRuleWeek_df = pd.DataFrame(days, columns=['day'])\n", - "logRuleWeek_df['case']= startCase * pow(2,(logRuleWeek_df['day'])/7)\n", - "logRuleWeek_df['doubling period']='every week'\n", - "\n", - "logRules_df = pd.concat([logRuleDay_df, logRule3Days_df, logRuleWeek_df])\n", - "logRules_df = logRules_df.reset_index()\n", - "\n", - "\n", - "ruleChart = alt.Chart(logRules_df).mark_line(opacity=0.2,clip=True).encode(\n", - " alt.X('day:Q',\n", - " scale=alt.Scale(domain=[1,max(death10_df.sinceDay0)+5])),\n", - " alt.Y('case', scale=alt.Scale(type='log',domain=[10,10000]),\n", - " ),\n", - " color = 'doubling period',\n", - " tooltip = ['doubling period']) \n", - "\n", - "# create a layer for the state labels\n", - "# 1) make dataframe with each state's max days\n", - "# 2) make a chart layer with text of state name to right of each state's rightmost point\n", - "stateLabels_df = death10_df[death10_df['sinceDay0'] == death10_df.groupby(['state'])['sinceDay0'].transform(max)]\n", - "labelChart = alt.Chart(stateLabels_df).mark_text(align='left', baseline='middle', dx=10).encode(\n", - " x='sinceDay0',\n", - " y='death',\n", - " text='state',\n", - " color='state')\n", - "\n", - "#now put the text labels layer on top of state labels Chart\n", - "labelChart = labelChart + alt.Chart(textLabels_df).mark_text(align='right', baseline='bottom', dx=0, size=18,opacity=0.5).encode(\n", - " x='labelX',\n", - " y='labelY',\n", - " text='labelText')\n", - "\n", - "\n", - "## Create some tooltip behavior - show Y values on mouseover\n", - "# Step 1: Selection that chooses nearest point based on value on x-axis\n", - "nearest = alt.selection(type='single', nearest=True, on='mouseover',\n", - " fields=['sinceDay0'])\n", - "\n", - "# Step 2: Transparent selectors across the chart. This is what tells us\n", - "# the x-value of the cursor\n", - "selectors = alt.Chart().mark_point().encode(\n", - " x=\"sinceDay0:Q\",\n", - " opacity=alt.value(0),\n", - ").add_selection(\n", - " nearest\n", - ")\n", - "\n", - "# Step 3: Add text, show values in column when it's the nearest point to \n", - "# mouseover, else show blank\n", - "text = lineChart.mark_text(align='center', dx=3, dy=-20).encode(\n", - " text=alt.condition(nearest, 'death', alt.value(' '))\n", - ")\n", - "\n", - "\n", - "#Finally, lets show the chart!\n", - "\n", - "chart = alt.layer(lineChart, ruleChart, labelChart, selectors, text, data=death10_df)\n", - "\n", - "display(chart)\n", - "display(html_credits)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "papermill": { - "duration": 0.736117, - "end_time": "2020-04-09T07:26:22.717908", - "exception": false, - "start_time": "2020-04-09T07:26:21.981791", - "status": "completed" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "<div id=\"altair-viz-130c367ce2a64e50b09715bcc283926e\"></div>\n", - "<script type=\"text/javascript\">\n", - " (function(spec, embedOpt){\n", - " const outputDiv = document.getElementById(\"altair-viz-130c367ce2a64e50b09715bcc283926e\");\n", - " const paths = {\n", - " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", - " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", - " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", - " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", - " };\n", - "\n", - " function loadScript(lib) {\n", - " return new Promise(function(resolve, reject) {\n", - " var s = document.createElement('script');\n", - " s.src = paths[lib];\n", - " s.async = true;\n", - " s.onload = () => resolve(paths[lib]);\n", - " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", - " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", - " });\n", - " }\n", - "\n", - " function showError(err) {\n", - " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", - " throw err;\n", - " }\n", - "\n", - " function displayChart(vegaEmbed) {\n", - " vegaEmbed(outputDiv, spec, embedOpt)\n", - " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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\"date\": \"2020-04-08T00:00:00\", \"state\": \"WY\", \"positive\": 221.0, \"negative\": 3843.0, \"pending\": null, \"hospitalizedCurrently\": null, \"hospitalizedCumulative\": 33.0, \"inIcuCurrently\": null, \"inIcuCumulative\": null, \"onVentilatorCurrently\": null, \"onVentilatorCumulative\": null, \"recovered\": 62.0, \"hash\": \"871dc959c9d38ea20b4d4c856b22997e0bccaf55\", \"dateChecked\": \"2020-04-08T20:00:00Z\", \"death\": 0.0, \"hospitalized\": 33.0, \"total\": 4064, \"totalTestResults\": 4064, \"posNeg\": 4064, \"fips\": 56, \"deathIncrease\": 0.0, \"hospitalizedIncrease\": 0.0, \"negativeIncrease\": 54.0, \"positiveIncrease\": 5.0, \"totalTestResultsIncrease\": 59.0, \"ratio\": 0.05437992125984252, \"sinceDay0\": 8}], \"data-0a08c6105da7e065c75198fff0e29db2\": [{\"labelX\": 9, \"labelY\": 30000, \"labelText\": \"doubles every day\"}, {\"labelX\": 28, \"labelY\": 31000, \"labelText\": \"doubles every 3 days\"}, {\"labelX\": 32, \"labelY\": 1000, \"labelText\": \"doubles every week\"}]}}, {\"mode\": \"vega-lite\"});\n", - "</script>" - ], - "text/plain": [ - "alt.LayerChart(...)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "<p style=\"font-size: smaller\">Data Sources: \n", - " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", - "<br>\n", - "Analysis and Visualization:\n", - " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", - "</p>" - ], - "text/plain": [ - "<IPython.core.display.HTML object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# make dataframe for text labels on chart - hand edit these label locations\n", - "textLabels_df = pd.DataFrame(\n", - " [[9,30000,'doubles every day'],\n", - " [28,31000,'doubles every 3 days'],\n", - " [32,1000, 'doubles every week']],\n", - " columns =['labelX', 'labelY','labelText']\n", - ")\n", - "\n", - "# make dataframe with only points >=100 positives\n", - "positive100_df = data_df.loc[data_df['positive']>=100]\n", - "\n", - "## add US to that dataframe\n", - "nationpos100_df = nation_df.loc[nation_df['positive']>=100]\n", - "positive100_df= pd.concat ([positive100_df,nationpos100_df])\n", - "\n", - "# group positive100 dataframe by state and then increasing order of date\n", - "positive100_df = positive100_df.sort_values(by=['state','date'])\n", - "positive100_df = positive100_df.reset_index()\n", - "\n", - "# make a list of the states with 10 or more deaths (don't really need this)\n", - "# state_list = list(set(positive100_df['state']))\n", - "\n", - "# add a column for the number of days since the 100th case for each state\n", - "for state, df in positive100_df.groupby('state'):\n", - " positive100_df.loc[df.index,'sinceDay0'] = range(0, len(df))\n", - "positive100_df = positive100_df.astype({'sinceDay0': 'int32'})\n", - "\n", - " \n", - "# Now create plotlines for each state since 10 deaths\n", - "lineChart = alt.Chart(positive100_df, title=\"US States: total cases since 100th case\").mark_line(interpolate='basis').encode(\n", - " alt.X('sinceDay0:Q', axis=alt.Axis(title='Days since 100th case')),\n", - " alt.Y('positive:Q',\n", - " axis = alt.Axis(title='Cumulative positive cases'),\n", - " scale=alt.Scale(type='log')),\n", - " tooltip=['state', 'sinceDay0', 'death', 'positive'],\n", - " color = 'state'\n", - ").properties(width=800,height=400)\n", - "\n", - "## Create a layer with the lines for doubling every day and doubling every week\n", - "# make dataframe with lines to indicate doubling every day, 3 days, week \n", - "\n", - "days = {'day':[1,2,3,4,5,10,15,20, max(positive100_df.sinceDay0)+5]}\n", - "startCase = 100\n", - "logRuleDay_df = pd.DataFrame (days, columns=['day'])\n", - "logRuleDay_df['case']= startCase * pow(2,logRuleDay_df['day'])\n", - "logRuleDay_df['doubling period']='every day'\n", - "\n", - "logRule3Days_df = pd.DataFrame (days, columns=['day'])\n", - "logRule3Days_df['case']= startCase * pow(2,(logRule3Days_df['day'])/3)\n", - "logRule3Days_df['doubling period']='three days'\n", - "\n", - "logRuleWeek_df = pd.DataFrame (days, columns=['day'])\n", - "logRuleWeek_df['case']= startCase * pow(2,(logRuleWeek_df['day'])/7)\n", - "logRuleWeek_df['doubling period']='every week'\n", - "\n", - "logRules_df = pd.concat([logRuleDay_df, logRule3Days_df, logRuleWeek_df])\n", - "logRules_df = logRules_df.reset_index()\n", - "\n", - "ruleChart = alt.Chart(logRules_df).mark_line(opacity=0.2,clip=True).encode(\n", - " alt.X('day:Q',\n", - " scale=alt.Scale(domain=[1, max(positive100_df.sinceDay0)+5])),\n", - " alt.Y('case', scale=alt.Scale(domain=[100,200000], type='log'),\n", - " ),\n", - " color = 'doubling period')\n", - "\n", - "# create a layer for the state labels\n", - "# 1) make dataframe with each state's max days\n", - "# 2) make a chart layer with text of state name to right of each state's rightmost point\n", - "stateLabels_df = positive100_df[positive100_df['sinceDay0'] == positive100_df.groupby(['state'])['sinceDay0'].transform(max)]\n", - "labelChart = alt.Chart(stateLabels_df).mark_text(align='left', baseline='middle', dx=10).encode(\n", - " x='sinceDay0',\n", - " y='positive',\n", - " text='state',\n", - " color='state')\n", - "\n", - "#now put the text labels layer on top of state labels Chart\n", - "labelChart = labelChart + alt.Chart(textLabels_df).mark_text(align='right', baseline='bottom', dx=0, size=18,opacity=0.5).encode(\n", - " x='labelX',\n", - " y='labelY',\n", - " text='labelText')\n", - "\n", - "#Create some tooltip behavior\n", - "# Step 1: Selection that chooses nearest point based on value on x-axis\n", - "nearest = alt.selection(type='single', nearest=True, on='mouseover',\n", - " fields=['sinceDay0'])\n", - "\n", - "# Step 2: Transparent selectors across the chart. This is what tells us\n", - "# the x-value of the cursor\n", - "selectors = alt.Chart().mark_point().encode(\n", - " x=\"sinceDay0:Q\",\n", - " opacity=alt.value(0),\n", - ").add_selection(\n", - " nearest\n", - ")\n", - "\n", - "# Step 3: Add text, show values in Sex column when it's the nearest point to \n", - "# mouseover, else show blank\n", - "text = lineChart.mark_text(align='center', dx=3, dy=-20).encode(\n", - " text=alt.condition(nearest, 'positive', alt.value(' '))\n", - ")\n", - "\n", - "\n", - "#Finally, lets show the chart!\n", - "\n", - "chart = alt.layer(lineChart, ruleChart, labelChart, selectors, text, data=death10_df)\n", - "#chart = alt.layer(lineChart, ruleChart, labelChart)\n", - "chart.properties (width=400,height=800)\n", - "display(chart)\n", - "display(html_credits)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "papermill": { - "duration": 0.054039, - "end_time": "2020-04-09T07:26:22.826562", - "exception": false, - "start_time": "2020-04-09T07:26:22.772523", - "status": "completed" - }, - "tags": [] - }, - "source": [ - "### Daily Cumulative Totals\n", - "\n", - "Cumulative reported totals of positive cases and deaths. " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "papermill": { - "duration": 0.152914, - "end_time": "2020-04-09T07:26:23.034814", - "exception": false, - "start_time": "2020-04-09T07:26:22.881900", - "status": "completed" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "<div id=\"altair-viz-49786738da48422a9628d1ba709b0aaf\"></div>\n", - "<script type=\"text/javascript\">\n", - " (function(spec, embedOpt){\n", - " const outputDiv = document.getElementById(\"altair-viz-49786738da48422a9628d1ba709b0aaf\");\n", - " const paths = {\n", - " \"vega\": \"https://cdn.jsdelivr.net/npm//vega@5?noext\",\n", - " \"vega-lib\": \"https://cdn.jsdelivr.net/npm//vega-lib?noext\",\n", - " \"vega-lite\": \"https://cdn.jsdelivr.net/npm//vega-lite@4.0.2?noext\",\n", - " \"vega-embed\": \"https://cdn.jsdelivr.net/npm//vega-embed@6?noext\",\n", - " };\n", - "\n", - " function loadScript(lib) {\n", - " return new Promise(function(resolve, reject) {\n", - " var s = document.createElement('script');\n", - " s.src = paths[lib];\n", - " s.async = true;\n", - " s.onload = () => resolve(paths[lib]);\n", - " s.onerror = () => reject(`Error loading script: ${paths[lib]}`);\n", - " document.getElementsByTagName(\"head\")[0].appendChild(s);\n", - " });\n", - " }\n", - "\n", - " function showError(err) {\n", - " outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n", - " throw err;\n", - " }\n", - "\n", - " function displayChart(vegaEmbed) {\n", - " vegaEmbed(outputDiv, spec, embedOpt)\n", - " .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. 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- " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", - "<br>\n", - "Analysis and Visualization:\n", - " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", - "</p>" - ], - "text/plain": [ - "<IPython.core.display.HTML object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "base = alt.Chart(\n", - " daily_totals\n", - ").mark_bar(size=7).encode(\n", - " alt.X('date', axis=alt.Axis(title='')\n", - " )\n", - ").properties(\n", - " height=200,\n", - " width=400\n", - ")\n", - "\n", - "cumulative = base.encode(alt.Y('positive', title = 'Cumulative cases'))\n", - "cumulative_deaths = base.encode(alt.Y('death', title = 'Cumulative deaths'))\n", - "rates = base.encode(alt.Y('positive_diff', title='Daily cases'))\n", - "rates_deaths = base.encode(alt.Y('death_diff', title='Daily deaths'))\n", - "chart = alt.vconcat(\n", - " cumulative | rates, cumulative_deaths | rates_deaths,\n", - " title='Cumulative Covid-19 cases and deaths in the U.S.'\n", - ").configure_title(\n", - " anchor='middle'\n", - ")\n", - "display(chart)\n", - "display(html_credits)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "papermill": { - "duration": 0.05519, - "end_time": "2020-04-09T07:26:23.149589", - "exception": false, - "start_time": "2020-04-09T07:26:23.094399", - "status": "completed" - }, - "tags": [] - }, - "source": [ - "### Total tests and positives per 100k population" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "papermill": { - "duration": 0.084063, - "end_time": "2020-04-09T07:26:23.286156", - "exception": false, - "start_time": "2020-04-09T07:26:23.202093", - "status": "completed" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Most recent test date 2020-04-08 00:00:00\n", - "56 states/territories have data on this date.\n" - ] - } - ], - "source": [ - "most_recent_test_date = data_df['date'].max()\n", - "most_recent_df = data_df[data_df['date'] == most_recent_test_date].set_index('state')\n", - "print(\"Most recent test date\", most_recent_test_date)\n", - "print(len(most_recent_df), \"states/territories have data on this date.\")\n", - "\n", - "most_recent_df['total/100k'] = (most_recent_df['total'] / pop_df['Population']) * 100000\n", - "most_recent_df['positive/100k'] = (most_recent_df['positive'] / pop_df['Population']) * 100000\n", - "most_recent_df = most_recent_df.reset_index()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "papermill": { - "duration": 0.147994, - "end_time": "2020-04-09T07:26:23.490399", - "exception": false, - "start_time": "2020-04-09T07:26:23.342405", - "status": "completed" - }, - "tags": [] - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "<div id=\"altair-viz-875f824c40184cbc986cb8bd121a21e3\"></div>\n", - "<script type=\"text/javascript\">\n", - " 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"display(alt.layer(tests, positives))\n", - "display(html_credits)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "papermill": { - "duration": 0.052685, - "end_time": "2020-04-09T07:26:23.604533", - "exception": false, - "start_time": "2020-04-09T07:26:23.551848", - "status": "completed" - }, - "tags": [] - }, - "source": [ - "## Counts and rates by state\n", - "\n", - "Taking a look at the three states with the highest per-capita incidence of covid-19. The red and yellow curves represent the total tests and total positive tests respectively. 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\"2020-03-06T00:00:00\", \"positive\": 8.0, \"negative\": null, \"pending\": null, \"hospitalizedCurrently\": null, \"hospitalizedCumulative\": null, \"inIcuCurrently\": null, \"inIcuCumulative\": null, \"onVentilatorCurrently\": null, \"onVentilatorCumulative\": null, \"recovered\": null, \"hash\": \"ba07a81180b3f869f4fc9a15473d56c77bda4a58\", \"dateChecked\": \"2020-03-06T21:00:00Z\", \"death\": null, \"hospitalized\": null, \"total\": 8, \"totalTestResults\": 8, \"posNeg\": 8, \"fips\": 25, \"deathIncrease\": 0.0, \"hospitalizedIncrease\": 0.0, \"negativeIncrease\": 0.0, \"positiveIncrease\": 6.0, \"totalTestResultsIncrease\": 6.0, \"ratio\": 1.0, \"positive_diff\": 6.0, \"negative_diff\": null, \"death_diff\": null, \"positive_diff_100k\": 0.08633710928680799, \"death_diff_100k\": null, \"total_10\": 0.8}, {\"state\": \"MA\", \"date\": \"2020-03-05T00:00:00\", \"positive\": 2.0, \"negative\": null, \"pending\": null, \"hospitalizedCurrently\": null, \"hospitalizedCumulative\": null, \"inIcuCurrently\": null, \"inIcuCumulative\": null, \"onVentilatorCurrently\": null, \"onVentilatorCumulative\": null, \"recovered\": null, \"hash\": \"ad6e88d352dfa8b8f0dd1bf41a2c506911f25bc0\", \"dateChecked\": \"2020-03-05T21:00:00Z\", \"death\": null, \"hospitalized\": null, \"total\": 2, \"totalTestResults\": 2, \"posNeg\": 2, \"fips\": 25, \"deathIncrease\": 0.0, \"hospitalizedIncrease\": 0.0, \"negativeIncrease\": 0.0, \"positiveIncrease\": 0.0, \"totalTestResultsIncrease\": 0.0, \"ratio\": 1.0, \"positive_diff\": 0.0, \"negative_diff\": null, \"death_diff\": null, \"positive_diff_100k\": 0.0, \"death_diff_100k\": null, \"total_10\": 0.2}, {\"state\": \"MA\", \"date\": \"2020-03-04T00:00:00\", \"positive\": 2.0, \"negative\": null, \"pending\": null, \"hospitalizedCurrently\": null, \"hospitalizedCumulative\": null, \"inIcuCurrently\": null, \"inIcuCumulative\": null, \"onVentilatorCurrently\": null, \"onVentilatorCumulative\": null, \"recovered\": null, \"hash\": \"36d8d4b1b34007477b562a078613309f63e7bd0e\", \"dateChecked\": \"2020-03-04T21:00:00Z\", \"death\": null, \"hospitalized\": null, \"total\": 2, \"totalTestResults\": 2, \"posNeg\": 2, \"fips\": 25, \"deathIncrease\": null, \"hospitalizedIncrease\": null, \"negativeIncrease\": null, \"positiveIncrease\": null, \"totalTestResultsIncrease\": null, \"ratio\": 1.0, \"positive_diff\": null, \"negative_diff\": null, \"death_diff\": null, \"positive_diff_100k\": null, \"death_diff_100k\": null, \"total_10\": 0.2}]}}, {\"mode\": \"vega-lite\"});\n", - "</script>" - ], - "text/plain": [ - "alt.HConcatChart(...)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "\n", - "<p style=\"font-size: smaller\">Data Sources: \n", - " <a href=\"https://covidtracking.com\">The COVID Tracking Project</a>\n", - "<br>\n", - "Analysis and Visualization:\n", - " <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n", - "</p>" - ], - "text/plain": [ - "<IPython.core.display.HTML object>" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# produce the charts for a few states\n", - "\n", - "charts=[]\n", - "for state in most_recent_df.sort_values('total/100k', ascending=False)['state'].to_list()[:3]: \n", - " state_df = tdf_diff[tdf_diff['state'] == state].copy()\n", - "\n", - " base = alt.Chart(state_df, title=state).encode(alt.X('date', axis=alt.Axis(title='Date'))).properties(width=250, height=150)\n", - " dailies = base.mark_bar(size=6).encode(alt.Y('positive_diff', axis=alt.Axis(title='Daily positive')))\n", - "\n", - " totals = base.mark_line(color='red').encode(alt.Y('total_10', axis=alt.Axis(title='Total/10'))) \n", - " positives = totals.mark_line(color='orange').encode(alt.Y('positive', axis=alt.Axis(title='Positive')))\n", - " cumulative = totals + positives\n", - "\n", - " ratio = base.mark_line(color='red').encode(alt.Y('ratio', axis=alt.Axis(title='Positive/Total'), scale=alt.Scale(domain=(0,1))))\n", - " \n", - " charts.append(alt.layer(dailies, cumulative).resolve_scale(y='independent'))\n", - "\n", - "display(alt.hconcat(*charts))\n", - "display(html_credits)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "papermill": { - "duration": 0.055858, - "end_time": "2020-04-09T07:26:24.104868", - "exception": false, - "start_time": "2020-04-09T07:26:24.049010", - "status": "completed" - }, - "tags": [] - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "hide_input": true, - "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": "3.7.3" - }, - "papermill": { - "duration": 5.062519, - "end_time": "2020-04-09T07:26:24.475172", - "environment_variables": {}, - "exception": null, - "input_path": "/tmp/yrqgj0hh/notebooks/covidtracking-dashboard.ipynb", - "output_path": "runs/covidtracking-dashboard.ipynb", - "parameters": { - "data_path": "/tmp/yrqgj0hh/data/covidtracking" - }, - "start_time": "2020-04-09T07:26:19.412653", - "version": "1.1.0" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} \ No newline at end of file