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Data-Science-For-Beginners/2-Working-With-Data/07-python/notebook-covidspread.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"source": [
"# Using Python for Data Processing\r\n",
"\r\n",
"## Tabular Data\r\n",
"\r\n",
"We will use data on COVID-19 infected individuals, provided by the [Center for Systems Science and Engineering](https://systems.jhu.edu/) (CSSE) at [Johns Hopkins University](https://jhu.edu/). Dataset is available in [this GitHub Repository](https://github.com/CSSEGISandData/COVID-19)."
],
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 1,
"source": [
"import numpy as np\r\n",
"import pandas as pd"
],
"outputs": [],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"We can load the most recent data directly from GitHub using `pd.read_csv`. If for some reason the data is not available, you can always use the copy available locally in the `data` folder - just uncomment lines below:"
],
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 4,
"source": [
"base_url = \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/\" # loading from Internet\r\n",
"# base_url = \"../../data/COVID/\" # loading from disk\r\n",
"infected_dataset_url = base_url + \"time_series_covid19_confirmed_global.csv\"\r\n",
"recovered_dataset_url = base_url + \"time_series_covid19_recovered_global.csv\"\r\n",
"deaths_dataset_url = base_url + \"time_series_covid19_deaths_global.csv\"\r\n",
"countries_dataset_url = base_url + \"../UID_ISO_FIPS_LookUp_Table.csv\""
],
"outputs": [],
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 5,
"source": [
"infected = pd.read_csv(infected_dataset_url)\r\n",
"infected.head()"
],
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