explore-owid-vaccinations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import datetime\n",
    "import pandas as pd\n",
    "import torch\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = os.path.expanduser(\"~/github/owid/covid-19-data/public/data/vaccinations/vaccinations.csv\")\n",
    "df = pd.read_csv(path, header=0)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "portion = df[\"total_vaccinations_per_hundred\"].to_numpy() / 100\n",
    "portion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations = df[\"location\"].to_list()\n",
    "location_id = sorted(set(locations))\n",
    "location_id = {name: i for i, name in enumerate(location_id)}\n",
    "locations = torch.tensor([location_id[n] for n in locations], dtype=torch.long)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def parse_date(s):\n",
    "    return datetime.datetime.strptime(s, \"%Y-%m-%d\")\n",
    "\n",
    "start_date = parse_date(\"2020-12-01\")\n",
    "dates = torch.tensor([(parse_date(d) - start_date).days\n",
    "                      for d in df[\"date\"]])\n",
    "assert dates.min() >= 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = int(1 + dates.max())\n",
    "R = len(location_id)\n",
    "dense_portion = torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.scatter(dates, portion, s=10, alpha=0.5);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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