From bc03ef22a0cfc90fe5ccfdb5a52181845aa3e8c7 Mon Sep 17 00:00:00 2001 From: Rok Roskar <rokroskar@gmail.com> Date: Thu, 9 Apr 2020 17:12:02 +0200 Subject: [PATCH] feat: add nytimes converter and example notebook --- notebooks/examples/us-nyt-covid-19.ipynb | 144 ++++++++++++++++++ .../covid_19_utils/covid_19_utils/__init__.py | 2 +- .../covid_19_utils/converters/nyt.py | 62 ++++++++ 3 files changed, 207 insertions(+), 1 deletion(-) create mode 100644 notebooks/examples/us-nyt-covid-19.ipynb create mode 100644 src/covid-19/covid_19_utils/covid_19_utils/converters/nyt.py diff --git a/notebooks/examples/us-nyt-covid-19.ipynb b/notebooks/examples/us-nyt-covid-19.ipynb new file mode 100644 index 000000000..af70e8023 --- /dev/null +++ b/notebooks/examples/us-nyt-covid-19.ipynb @@ -0,0 +1,144 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# COVID-19 Case data for U.S. from the New York Times\n", + "\n", + "Data from the [New York Times Covid-19 case database](https://github.com/nytimes/covid-19-data).\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import altair as alt\n", + "\n", + "from IPython.display import display, HTML\n", + "\n", + "from covid_19_utils import helper, plotting\n", + "from covid_19_utils.converters import CaseConverter" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "html_credits=HTML('''\n", + "<p style=\"font-size: smaller\">Data Sources: \n", + " <a href=\"https://github.com/nytimes/covid-19-data\">New York Times</a>, <a href=\"https://www.census.gov/\">U.S. Census</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": 4, + "metadata": {}, + "outputs": [], + "source": [ + "data_folder = \"../../data/covid-19-us-nyt/\"\n", + "converter = CaseConverter('../../data/atlas')\n", + "df = converter.read_convert(data_folder).rename(columns={'region_label':'state', 'admin2_label': 'county'})\n", + "df['county_state'] = df.apply(lambda row: f\"{row['county']}, {row['state']}\", axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# determine the top ten most affected counties\n", + "\n", + "latest_dt = df.date.iloc[-1]\n", + "top10 = df[df.date==latest_dt].sort_values(by='positive',ascending=False).iloc[:10]['county_state'].to_list()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": "\n<div id=\"altair-viz-8bc8c3f9104342a4894669ed4b5dcd10\"></div>\n<script type=\"text/javascript\">\n (function(spec, embedOpt){\n const outputDiv = document.getElementById(\"altair-viz-8bc8c3f9104342a4894669ed4b5dcd10\");\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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{\"mode\": \"vega-lite\"});\n</script>", + "text/plain": "alt.Chart(...)" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "<IPython.core.display.HTML object>", + "text/html": "\n<p style=\"font-size: smaller\">Data Sources: \n <a href=\"https://github.com/nytimes/covid-19-data\">New York Times</a>, <a href=\"https://www.census.gov/\">U.S. Census</a>\n<br>\nAnalysis and Visualization:\n <a href=\"https://renkulab.io/projects/covid-19/covid-19-public-data\">Covid-19 Public Data Collaboration Project</a>\n</p>" + }, + "metadata": {} + } + ], + "source": [ + "base = alt.Chart(df[df['county_state'].isin(top10)], title=\"Covid-19 Cases per 100k population in Top 10 U.S. Counties\")\n", + "\n", + "chart = plotting.generate_region_chart(\n", + " base, \n", + " 'positive_100k', \n", + " 'county_state', \n", + " 'Cases per 100k population', \n", + " 'Cases/100k', \n", + " scale_type='symlog'\n", + ")\n", + "\n", + "display(chart)\n", + "display(html_credits)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "hide_input": true, + "kernelspec": { + "display_name": "Python 3.7.7 64-bit ('.venv': venv)", + "language": "python", + "name": "python37764bitvenvvenv814492364d964019a25eb1cf3dc3e99c" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7-final" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/src/covid-19/covid_19_utils/covid_19_utils/__init__.py b/src/covid-19/covid_19_utils/covid_19_utils/__init__.py index 8c5400c2a..47beb193c 100644 --- a/src/covid-19/covid_19_utils/covid_19_utils/__init__.py +++ b/src/covid-19/covid_19_utils/covid_19_utils/__init__.py @@ -4,4 +4,4 @@ __author__ = """Chandrasekhar Ramakrishnan""" __email__ = "cramakri@ethz.ch" __version__ = "0.1.0" -from .converters import covidtracking, italy, jhu, spain, switzerland +from .converters import covidtracking, italy, jhu, nyt, spain, switzerland diff --git a/src/covid-19/covid_19_utils/covid_19_utils/converters/nyt.py b/src/covid-19/covid_19_utils/covid_19_utils/converters/nyt.py new file mode 100644 index 000000000..81709b13f --- /dev/null +++ b/src/covid-19/covid_19_utils/covid_19_utils/converters/nyt.py @@ -0,0 +1,62 @@ +""" +Covid-19 converters for data from the New York Times. + +Data source: https://github.com/nytimes/covid-19-data +""" + +from pathlib import Path + +import numpy as np +import pandas as pd + +from . import CaseConverterImpl as CaseConverter +from .. import helper + + +class NYTCaseConverter(CaseConverter): + """ + Converter for data from the U.S., collected by + the New York Times and hosted at https://github.com/nytimes/covid-19-data/ + """ + + conversion_dict = { + "county": "admin2_label", + "state": "region_label", + "cases": "positive", + "deaths": "deceased", + } + column_list = ["date", "county", "state", "fips", "cases", "deaths"] + + def convert(self, df): + # rename the existing columns + df_conv = df.rename(columns=self.conversion_dict) + df_conv["country"] = "USA" + df_conv["country_label"] = "United States of America" + df_conv["tested"] = np.nan + df_conv["date"] = pd.to_datetime(df_conv["date"]) + # get population data + pop = pd.read_csv(self.atlas_folder / "us_census/co-est2019-alldata.csv") + pop["fips"] = pop.STATE * 1000 + pop.COUNTY + merged = df_conv.merge(pop[["fips", "POPESTIMATE2019"]]).rename( + columns={"POPESTIMATE2019": "population"} + ) + + # add NYC manually based on https://github.com/nytimes/covid-19-data#geographic-exceptions + nyc_county_fips = [61, 47, 81, 5, 85] + nyc_pop = nyc_pop = pop.loc[ + (pop.STATE == 36) & (pop.COUNTY.isin(nyc_county_fips)) + ]["POPESTIMATE2019"].sum() + + merged = merged.append( + df_conv[df_conv.admin2_label == "New York City"], ignore_index=True + ) + merged.loc[merged.admin2_label == "New York City", "population"] = nyc_pop + + return self._set_common_columns(merged) + + def read_data(self, path): + """Read in the county data.""" + return pd.read_csv(Path(path) / "us-counties.csv") + + +NYTCaseConverter._register() -- GitLab