cv19_weekly.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Covid-19 Dashboard\n",
    "---\n",
    "\n",
    "Analysis of Covid-19 cases based on data reported on the European CDC website. This version supports the new format and weekly publication that came into effect from Dec 2020.\n",
    "\n",
    "Quick link to the [Dashboard](#dashboard)\n",
    "\n",
    "**Modification history:**\n",
    "- Updated to support new weekly version\n",
    "\n",
    "---\n",
    "\n",
    "Chandranath Gunjal (github.com/cdragun)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code <a id='code_section'></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import os.path\n",
    "import requests\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import IPython.display as ipd\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "sns.set(style='whitegrid', context='notebook', palette='muted')\n",
    "\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.precision', 10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fetch file and data cleaning\n",
    "def fetch_ECDC_data(url):\n",
    "    \"\"\"Fetch data from ECDC website - assumes that the data returned is in json format\"\"\"\n",
    "    # fetch data\n",
    "    response = requests.get(url, allow_redirects=True)\n",
    "    if not response.ok:\n",
    "        response.raise_for_status()\n",
    "\n",
    "    # load into data frame\n",
    "    return pd.read_json(response.content, typ='frame')\n",
    "\n",
    "\n",
    "def load_data(asof, url):\n",
    "    \"\"\"Read local filename if it exists - otherwise fetch from ECDC website\"\"\"\n",
    "    # file name spec for the cached (cleaned) data\n",
    "    def local_filename(x): return 'ecdc_' + x.replace('-', '_') + '.csv'\n",
    "    \n",
    "    try:\n",
    "        # read local file if it exists\n",
    "        print('trying local')\n",
    "        df = pd.read_csv(local_filename(asof), index_col=False) # na_filter=False\n",
    "        data_asof = asof\n",
    "\n",
    "    except Exception as exc:\n",
    "        print(f'exception raised ({exc}). trying remote')\n",
    "        df = cleanse_ECDC_data(fetch_ECDC_data(url))\n",
    "        data_asof = df['week'].max()\n",
    "        \n",
    "        fname = local_filename(data_asof)\n",
    "        if not os.path.exists(fname):\n",
    "            print(f'caching data to {fname}')\n",
    "            df.to_csv(local_filename(data_asof), index=False)\n",
    "        else:\n",
    "            print(f'cache [{fname}] already exists. not overwritten')\n",
    "\n",
    "    return df, data_asof\n",
    "        \n",
    "    \n",
    "def cleanse_ECDC_data(df):\n",
    "    \"\"\"Cleanse and reformat ECDC data\"\"\"\n",
    "    # work on a copy\n",
    "    ndf = df.copy()\n",
    "    \n",
    "    # rename columns\n",
    "    rv = {'country_code': 'cid', 'year_week': 'week'}\n",
    "    c = [rv[k] if k in rv else k for k in (i.lower() for i in ndf.columns)]\n",
    "    ndf.columns = c\n",
    "    \n",
    "    # drop continents data\n",
    "    ndf = ndf.dropna(axis=0)\n",
    "    \n",
    "    # collect static information - to re-insert after pivoting the indicator\n",
    "    countries = dict(zip(ndf['cid'], ndf['country']))\n",
    "    populations = dict(zip(ndf['cid'], ndf['population']))\n",
    "    continents = dict(zip(ndf['cid'], ndf['continent']))\n",
    "\n",
    "    ndf = ndf.pivot(['cid', 'week'], columns=['indicator'], values='weekly_count')\n",
    "    ndf = ndf.reset_index()\n",
    "    \n",
    "    ndf['country'] = [countries[c] for c in ndf['cid']]\n",
    "    ndf['population'] = [populations[c] for c in ndf['cid']]\n",
    "    ndf['continent'] = [continents[c] for c in ndf['cid']]\n",
    "    ndf.columns.name = None\n",
    "\n",
    "    # sort by country and week\n",
    "    ndf.sort_values(by=['cid', 'week'], ascending=[True, True],\n",
    "                    axis=0, inplace=True, ignore_index=True)\n",
    "    \n",
    "    # append global totals\n",
    "    ndf = ndf.append(compute_global_totals(ndf, 'W_'), ignore_index=True)\n",
    "\n",
    "    # append cumulative counts\n",
    "    ndf['cum_cases'] = ndf.groupby(['cid'])['cases'].cumsum()\n",
    "    ndf['cum_deaths'] = ndf.groupby(['cid'])['deaths'].cumsum()\n",
    "    return ndf\n",
    "\n",
    "\n",
    "def compute_global_totals(df, prefix):\n",
    "    \"\"\"Return dataframe with by-continent and world-wide statistics\"\"\"\n",
    "    if df['cid'].str.startswith(prefix).any():\n",
    "        raise ValueError('duplicate error: world stats already exist in dataframe')\n",
    "        \n",
    "    # consolidate by continent. cid = prefix + first two letters of continent name\n",
    "    cc = df.groupby(['continent', 'week'], as_index=False).sum()\n",
    "    cc['country'] = cc['continent']\n",
    "    cc['cid'] = prefix + cc['continent'].str[:2].str.upper()\n",
    "   \n",
    "    # worldwide numbers\n",
    "    ww = df.groupby(['week'], as_index=False).sum()\n",
    "    ww['country'] = 'World'\n",
    "    ww['continent'] = 'World'\n",
    "    ww['cid'] = prefix + 'WW'\n",
    "    return pd.concat([cc, ww])\n",
    "\n",
    "\n",
    "def fix_missing_numeric(df, col, fillval=0):\n",
    "    \"\"\"Fill blanks and NAs with zeroes\"\"\"\n",
    "    m = df[col].eq('')\n",
    "    df.loc[m, col] = fillval\n",
    "    df[col] = df[col].fillna(fillval)\n",
    "    return\n",
    "\n",
    "\n",
    "def lookup_country(df, substr):\n",
    "    \"\"\"Lookup a country name or cid. Empty string prints full list\"\"\"\n",
    "    substr, n = substr.upper(), len(substr)\n",
    "    \n",
    "    # simple search - either matches cid or beginning of country name\n",
    "    all_names = dict(sorted(zip(df['cid'], df['country'])))\n",
    "    subset = {id:name for id, name in all_names.items() \\\n",
    "              if substr == id or substr == name.upper()[:n]}\n",
    "    \n",
    "    # display\n",
    "    for i, (id, name) in enumerate(subset.items(), 1):\n",
    "        print('{: <26}'.format((id + ': ' + name)[:24]), end='')\n",
    "        if i % 3 == 0: print()\n",
    "    print()\n",
    "    return\n",
    "\n",
    "\n",
    "def week_of_year(dt=None):\n",
    "    \"\"\"Returns a string in yyyy-ww format for date given (or today)\"\"\"\n",
    "    if dt is None: dt = datetime.date.today()\n",
    "    \n",
    "    y, w, _ = datetime.date.isocalendar(dt)\n",
    "    return '{:d}-{:02d}'.format(y, w)\n",
    "\n",
    "\n",
    "def diff_in_weeks(d1, d2):\n",
    "    \"\"\"Difference in weeks for d1 and d2 (in yyyy-ww string format)\"\"\"\n",
    "    if d1 > d2: d1, d2 = d2, d1\n",
    "    \n",
    "    y1, w1 = map(int, d1.split('-'))\n",
    "    y2, w2 = map(int, d2.split('-'))\n",
    "    \n",
    "    return 52 * (y2 - y1) + (w2 - w1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Statistics / computations\n",
    "def compute_timeline(df, threshold, col, new_col):\n",
    "    \"\"\"Count periods from when a variable crossed a given threshold. Creates a new column in df\"\"\"\n",
    "    df[new_col] = 0\n",
    "    df.loc[df[col] >= threshold, new_col] = 1\n",
    "    df[new_col] = df.groupby(['cid'])[new_col].cumsum()\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_fatality_ratio(df, lag, new_col, num_col='cum_deaths', denom_col='cum_cases'):\n",
    "    \"\"\"Compute fatality ratio with a given lag. Creates a new column in given df\"\"\"                    \n",
    "    def shifted_fr(x):\n",
    "        x[new_col] = (x[num_col] / x[denom_col].shift(lag)).fillna(0).replace(np.inf, 0)\n",
    "        return x\n",
    "        \n",
    "    df[new_col] = df.groupby(['cid']).apply(shifted_fr)[new_col]\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_growth_rate(df, lag, col, new_col, dbl_col):\n",
    "    \"\"\"Compute average growth rate of a variable. Creates new columns in df\"\"\"\n",
    "    def growth_rate(x):\n",
    "        x[new_col] = (x[col] / x[col].shift(lag)).pow(1.0/lag).sub(1).\\\n",
    "                        fillna(0).replace(np.inf, 0)\n",
    "        return x\n",
    "    \n",
    "    df[new_col] = df.groupby(['cid']).apply(growth_rate)[new_col]\n",
    "    df[dbl_col] = (np.log(2) / np.log(df[new_col].add(1))).\\\n",
    "                        fillna(0).replace(np.inf, 0)\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_percapita_stat(df, col, new_col, base=1e6):\n",
    "    \"\"\"Rebase statistic to per unit of population\"\"\"\n",
    "    df[new_col] = df[col].div(df['population']).mul(base).\\\n",
    "                        fillna(0).replace(np.inf, 0)\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_ma(df, window, col, new_col):\n",
    "    \"\"\"Compute moving average of a given column\"\"\"\n",
    "    df[new_col] = df.groupby(['cid'])[col].apply(lambda s: s.rolling(window).mean()).\\\n",
    "                        fillna(0)\n",
    "    return\n",
    "\n",
    "\n",
    "def compute_stats(df, threshold, avg_period, lag):\n",
    "    \"\"\"Run all computations\"\"\"\n",
    "    # Create a timeline - first day when cum_cases exceeded a threshold\n",
    "    compute_timeline(df, threshold, 'cum_cases', 'timeline')\n",
    "\n",
    "    # compute fatality ratios - both cumulative and spot\n",
    "    df['daily_cases'] = df['cases'].div(7.0).round(0)\n",
    "    df['daily_deaths'] = df['deaths'].div(7.0).round(0)\n",
    "    compute_fatality_ratio(df, 0, 'fatality', 'cum_deaths', 'cum_cases')\n",
    "    compute_fatality_ratio(df, lag, 'fr_spot', 'deaths', 'cases')\n",
    "\n",
    "    # compute n-day growth rates and doubling times\n",
    "    compute_growth_rate(df, avg_period, 'cum_cases', 'gr_cases', 'dbl_cases')\n",
    "    compute_growth_rate(df, avg_period, 'cum_deaths', 'gr_deaths', 'dbl_deaths')\n",
    "    \n",
    "    # compute cum cases/deaths per million of population\n",
    "    compute_percapita_stat(df, 'cum_cases', 'pm_cases', 1e6)\n",
    "    compute_percapita_stat(df, 'cum_deaths', 'pm_deaths', 1e6)\n",
    "    \n",
    "    # moving average of daily cases / deaths\n",
    "    # compute_ma(df, avg_period, 'cases', 'ma_cases')\n",
    "    # compute_ma(df, avg_period, 'deaths', 'ma_deaths')\n",
    " \n",
    "    # sort out column order\n",
    "    df = pd.DataFrame(df, columns=['week', 'country', 'cid', 'timeline',\n",
    "                                   'continent', 'population',\n",
    "                                   'cases', 'deaths', 'daily_cases', 'daily_deaths',\n",
    "                                   'cum_cases', 'cum_deaths', 'pm_cases', 'pm_deaths',\n",
    "                                   'fatality','fr_spot',\n",
    "                                   'gr_cases', 'dbl_cases', 'gr_deaths', 'dbl_deaths'])\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reports\n",
    "\n",
    "nice_names = {'week': 'Week', 'country': 'Country', 'cid': 'CID',\n",
    "              'cases': 'Weekly Cases', 'deaths': 'Weekly Deaths',\n",
    "              'population': 'Population',\n",
    "              'cum_cases': 'Cum. Cases', 'cum_deaths': 'Cum. Deaths', \n",
    "              'timeline': 'Timeline',\n",
    "              'fatality': 'Fatality',   'fr_spot': 'Fatality (spot)',\n",
    "              'gr_cases': 'Growth-r Cases', 'gr_deaths': 'Growth-r Deaths',\n",
    "              'pm_cases': 'Cases (pm)',  'pm_deaths': 'Deaths (pm)',\n",
    "              'daily_cases': 'Daily Cases',    'daily_deaths': 'Daily Deaths',\n",
    "              'dbl_cases': 'Double-t Cases', 'dbl_deaths': 'Double-t Deaths'\n",
    "             }\n",
    "\n",
    "fmt_style = {'week': '{:s}',          'cases': '{:,.0f}',\n",
    "             'deaths': '{:,.0f}',     'population': '{:,.0f}',\n",
    "             'cum_cases': '{:,.0f}',  'cum_deaths': '{:,.0f}', \n",
    "             'fatality': '{:.2%}',    'fr_spot': '{:.2%}',\n",
    "             'gr_cases': '{:.2%}',    'gr_deaths': '{:.2%}',\n",
    "             'pm_cases': '{:,.0f}',   'pm_deaths': '{:,.0f}',\n",
    "             'daily_cases': '{:,.0f}',  'daily_deaths': '{:,.0f}',\n",
    "             'dbl_cases': '{:,.0f}',    'dbl_deaths': '{:,.0f}',\n",
    "             }\n",
    "\n",
    "\n",
    "def make_nice_names(names):\n",
    "    \"\"\"Return nice names for given list\"\"\"\n",
    "    return [nice_names[c] if c in nice_names else c.capitalize() for c in names]\n",
    "\n",
    "\n",
    "def spruce(df, show_cols=[], hide_cols=[], show_nice_names=False):\n",
    "    \"\"\"Spruce up index & columns for displaying a dataframe\"\"\"\n",
    "    # choose columns to show\n",
    "    all_cols = show_cols if len(show_cols) > 0 else list(df.columns)\n",
    "    for c in hide_cols:\n",
    "        if c in all_cols:\n",
    "            all_cols.remove(c)\n",
    "    \n",
    "    y = pd.DataFrame(df, columns=all_cols)\n",
    " \n",
    "    # pretty up index and columns names\n",
    "    y.index = np.arange(1, len(df) + 1)\n",
    "    if show_nice_names: y.columns = make_nice_names(all_cols)\n",
    "    return y\n",
    "\n",
    "\n",
    "def stylise(df, show_nice_names=False):\n",
    "    \"\"\"Apply styles to dataframe\"\"\"\n",
    "    return df.style.format({nice_names[c]:f for c,f in fmt_style.items()}\n",
    "                                if show_nice_names else fmt_style)\n",
    "    \n",
    "    \n",
    "def rpt_show(df, caption, asof=None, sortby=None, count=0,\n",
    "             hide_cols=['population'], show_nice_names=False):\n",
    "    \"\"\"Show part of a dataframe\"\"\"\n",
    "    if count == 0: count = len(df)\n",
    "\n",
    "    y = df\n",
    "    if asof is not None: y = y[y.week == asof]\n",
    "    if sortby is not None: y = y.sort_values([sortby], ascending=False)\n",
    "    \n",
    "    # show report \n",
    "    print('\\n', caption, '\\n')\n",
    "    y = spruce(y.head(count), hide_cols=hide_cols, show_nice_names=show_nice_names)\n",
    "    ipd.display(stylise(y, show_nice_names=show_nice_names))\n",
    "    return\n",
    "\n",
    "\n",
    "def rpt_stats(df, asof, variables, filter_col='cum_deaths', threshold=100,\n",
    "              sort_ascending=False, count=10, show_nice_names=False):\n",
    "    \"\"\"Stats report\"\"\"\n",
    "    main_cols = ['country', 'cid']\n",
    "    \n",
    "    sections = []\n",
    "    for i, v in enumerate(variables, 1):\n",
    "        x = df[(df[filter_col] > threshold) & (df['week'] == asof) &\n",
    "                      (~ df['cid'].str.startswith('W_'))]\\\n",
    "                   .sort_values([v], ascending=sort_ascending)\\\n",
    "                   .head(count)\n",
    "        \n",
    "        x = spruce(x, main_cols + [v])\n",
    "        x.columns = [c + str(i) for c in main_cols] + [v]\n",
    "        sections.append(x)\n",
    "    y = pd.concat(sections, axis=1)\n",
    "    if show_nice_names: y.columns = make_nice_names(y.columns)\n",
    "\n",
    "    print('\\n', 'Statistics for ' + asof, '\\n')\n",
    "    ipd.display(stylise(y, show_nice_names=show_nice_names))\n",
    "    return\n",
    "\n",
    "\n",
    "def rpt_history(df_all, cid, *, history=7, show_nice_names=False):\n",
    "    \"\"\"Show n-period history for given cid\"\"\"\n",
    "    \n",
    "    # show history\n",
    "    df = df_all[(df_all.cid == cid) & (df_all.timeline > 0)]\n",
    "    if len(df) < 2:\n",
    "        print(\"Insufficient data for requested country\")\n",
    "        return\n",
    "    \n",
    "    caption = '{} ({}), pop. {:,}: Last {} weeks. Timeline: Week-{}'.\\\n",
    "               format(df['country'].iloc[0], cid, df['population'].max(),\n",
    "                      history, df['timeline'].max())\n",
    "    rpt_show(df.tail(history)[::-1], caption,\n",
    "             hide_cols=['country', 'cid', 'population', 'continent'],\n",
    "             show_nice_names=show_nice_names)\n",
    "    return\n",
    "\n",
    "\n",
    "def rpt_country(df_all, cid, *, history=7, show_nice_names=False):\n",
    "    \"\"\"Summary report for given country\"\"\"\n",
    "    \n",
    "    # show history\n",
    "    rpt_history(df_all, cid, history=history, show_nice_names=show_nice_names)\n",
    "\n",
    "    # show charts\n",
    "    df = df_all[(df_all.cid == cid) & (df_all.timeline > 0)]\n",
    "    if len(df) < 2:\n",
    "        print(\"Insufficient data for requested country\")\n",
    "        return None\n",
    "  \n",
    "    plt.figure(1, figsize=(18, 21))\n",
    "    ax = plt.subplot(321)\n",
    "    df.plot(ax=ax, x='timeline', y=['cum_cases'], marker='.')\n",
    "\n",
    "    ax = plt.subplot(322)\n",
    "    df.plot(ax=ax, x='timeline', y=['cum_deaths'], marker='.')\n",
    "\n",
    "    ax = plt.subplot(323)\n",
    "    df.plot(ax=ax, x='timeline', y='daily_cases', kind='line', marker='.')\n",
    "    df.plot(ax=ax, x='timeline', y='gr_cases', secondary_y='gr_cases', kind='line', marker='.')\n",
    "    ax.right_ax.set_ylim(0, 0.5)\n",
    "                             \n",
    "    ax = plt.subplot(324)\n",
    "    df.plot(ax=ax, x='timeline', y='daily_deaths', kind='line', marker='.')\n",
    "    df.plot(ax=ax, x='timeline', y='gr_deaths', secondary_y='gr_deaths', kind='line', marker='.')\n",
    "    ax.right_ax.set_ylim(0, 0.5)\n",
    "\n",
    "    ax = plt.subplot(325)\n",
    "    df.plot(ax=ax, x='timeline', y=['fatality', 'fr_spot'], marker='.')\n",
    "    ax.set_ylim(0, 0.2)\n",
    "\n",
    "    ax = plt.subplot(326)\n",
    "    df.plot(ax=ax, x='timeline', y=['dbl_cases', 'dbl_deaths'], marker='.')\n",
    "\n",
    "    plt.show()\n",
    "    return\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# charts\n",
    "def chart(df, title, *, cid, x, y, log_scale=None, filter_timeline=False,\n",
    "          figsize=(16,8), **kwargs):\n",
    "    \"\"\"Generic charting routine\n",
    "    \n",
    "    cid:             a single cid or a list\n",
    "    x:               x-axis column\n",
    "    y:               y-axis column(s)\n",
    "    log_scale:       scale axis on a log scale; valid values are None, x, y or both\n",
    "    filter_timeline: additionally filter data for timeline > 0\n",
    "    \n",
    "    Note that both cid and y cannot be lists.\n",
    "    \"\"\"\n",
    "    # check parameters\n",
    "    if np.isscalar(cid):\n",
    "        cid = [cid]\n",
    "    if np.isscalar(y):\n",
    "        y = [y]\n",
    "    assert len(cid) == 1 or len(y) == 1, 'Both cid and y cannot be arraylike'\n",
    "    \n",
    "    # log graph?\n",
    "    p_logx = log_scale == 'x'\n",
    "    p_logy = log_scale == 'y'\n",
    "    p_loglog = log_scale == 'both'\n",
    "\n",
    "    # filter data\n",
    "    mask = df['cid'].isin(cid)\n",
    "    if x == 'timeline' or filter_timeline:\n",
    "        mask &= df['timeline'] > 0\n",
    "\n",
    "    needed_cols = [x] + y\n",
    "    cnames = dict(zip(df['cid'], df['country']))   # TODO: Refactor\n",
    "\n",
    "    # create the chart\n",
    "    plt.figure(1, figsize=figsize)\n",
    "    ax = plt.subplot(111)\n",
    "    for c in cid:\n",
    "        lbl = y if len(cid) == 1 else [cnames.get(c, c)]\n",
    "        data = pd.DataFrame(df[mask & (df['cid'] == c)], columns=needed_cols)\n",
    "        data.plot(ax=ax, x=x, y=y, label=lbl, logx=p_logx, logy=p_logy, loglog=p_loglog, **kwargs)\n",
    "\n",
    "    plt.title(title)\n",
    "    plt.show()\n",
    "    return\n",
    "\n",
    "\n",
    "def timeline_chart(df, title, *, cid, y, log_scale=None, **kwargs):\n",
    "    \"\"\"Chart variable for given countries\"\"\"\n",
    "    chart(df, title, cid=cid, x='timeline', y=y, log_scale=log_scale, **kwargs)\n",
    "    return\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dashboard <a id='dashboard'></a>\n",
    "\n",
    "- This will fetch the data from the ECDC website and save a clean (dated) version in the local directory\n",
    "- Subsequent loads will read the local version if it exists.\n",
    "\n",
    "\n",
    "Click here to go to the [Code section](#code_section)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# general parameters\n",
    "# ------------------\n",
    "# ECDC website - caveat, the file's name format changes every so often\n",
    "url1 = 'https://opendata.ecdc.europa.eu/covid19/nationalcasedeath/json'\n",
    "\n",
    "# Week0 for each country is determined when cum_cases >= threshold\n",
    "timeline_threshold = 100\n",
    "\n",
    "# Period over which to compute the average growth rate\n",
    "avg_period = 2\n",
    "\n",
    "# Lag to use for fatality ratio\n",
    "lag = 2\n",
    "\n",
    "# subsets of interest\n",
    "home = 'GBR'\n",
    "world = 'W_WW'\n",
    "monitor = ['W_WW', 'USA', 'BRA', 'GBR', 'ITA', 'ESP', 'DEU', 'FRA', 'CHE', 'SWE',\n",
    "           'CHN', 'JPN', 'KOR', 'RUS', 'IND']\n",
    "continents = ['W_WW', 'W_AS', 'W_EU', 'W_AM', 'W_AF', 'W_OC']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Weekly update\n",
    "\n",
    "Change asof to the current week and re-run all cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trying local\n",
      "loaded data asof 2021-32 vs requested 2021-32 for the current week 2021-34\n"
     ]
    }
   ],
   "source": [
    "# Load data and update asof to latest week. Can't automate the local caching efficiently\n",
    "# as there is no timestamp info on the website - have to download the full time series\n",
    "# to work it out. The data is updated at some time every Thursday\n",
    "request_week = '2021-32'\n",
    "curr_week = week_of_year()\n",
    "\n",
    "df, asof = load_data(curr_week if diff_in_weeks(request_week, curr_week) > 2 else request_week, url1)\n",
    "print('loaded data asof {} vs requested {} for the current week {}'.format(asof, request_week, curr_week))\n",
    "df = compute_stats(df, timeline_threshold, avg_period, lag)\n",
    "\n",
    "# data subsets \n",
    "df_world = df[df['cid'] == world]\n",
    "df_home  = df[df['cid'] == home]\n",
    "df_mon   = df[df['cid'].isin(monitor)]\n",
    "df_continents = df[df['cid'].isin(continents)]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Description of column names\n",
    "---\n",
    "- *cid:* Geographic ID. WW has been included for World statistics\n",
    "- *timeline:* Day-1 is the first day that cum_cases for a country exceeds a certain threshold (defined by timeline_threshold; see above)\n",
    "\n",
    "\n",
    "- *cases:* Cases reported for the given week\n",
    "- *daily_cases:* Cases/day for the week \n",
    "- *cum_cases:* Cumulative cases up to the given week\n",
    "- *pm_cases:* Total cases per million of population\n",
    "\n",
    "\n",
    "- *deaths:* Deaths reported for the given week\n",
    "- *daily_deaths:* Deaths/day for the week\n",
    "- *cum_deaths:* Cumulative deaths up to the given week\n",
    "- *pm_deaths:* Total deaths per million of population\n",
    "\n",
    "\n",
    "- *fatality:* Fatality rate (%age) based on cumulative statistics i.e. cum_deaths(t) / cum_cases(t)\n",
    "- *fr_spot:* Spot fatality rate based on recent statistics i.e. deaths(t) / cases(t - lag)\n",
    "\n",
    "\n",
    "- *gr_cases:* The growth rate (%age) in cases reported. This is a 3-day compounded moving average to smoothen the data\n",
    "- *gr_deaths:* The growth rate (%age) in deaths reported. Computed similar to gr_cases\n",
    "- *dbl_cases:* Days for cumulative cases reported to double in number. Implied from the growth rate; therefore lagging because of the averaging period used\n",
    "- *dbl_deaths:* Days for cumulative deaths reported to double in number\n",
    "\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monitor\n",
    "\n",
    "Statistics for countries in the monitor list "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics by continent for: 2021-32 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_ea594_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country</th>        <th class=\"col_heading level0 col1\" >Timeline</th>        <th class=\"col_heading level0 col2\" >Weekly Cases</th>        <th class=\"col_heading level0 col3\" >Weekly Deaths</th>        <th class=\"col_heading level0 col4\" >Daily Cases</th>        <th class=\"col_heading level0 col5\" >Daily Deaths</th>        <th class=\"col_heading level0 col6\" >Cum. Cases</th>        <th class=\"col_heading level0 col7\" >Cum. Deaths</th>        <th class=\"col_heading level0 col8\" >Cases (pm)</th>        <th class=\"col_heading level0 col9\" >Deaths (pm)</th>        <th class=\"col_heading level0 col10\" >Fatality</th>        <th class=\"col_heading level0 col11\" >Fatality (spot)</th>        <th class=\"col_heading level0 col12\" >Growth-r Cases</th>        <th class=\"col_heading level0 col13\" >Double-t Cases</th>        <th class=\"col_heading level0 col14\" >Growth-r Deaths</th>        <th class=\"col_heading level0 col15\" >Double-t Deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_ea594_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_ea594_row0_col0\" class=\"data row0 col0\" >World</td>\n",
       "                        <td id=\"T_ea594_row0_col1\" class=\"data row0 col1\" >83</td>\n",
       "                        <td id=\"T_ea594_row0_col2\" class=\"data row0 col2\" >4,452,173</td>\n",
       "                        <td id=\"T_ea594_row0_col3\" class=\"data row0 col3\" >67,204</td>\n",
       "                        <td id=\"T_ea594_row0_col4\" class=\"data row0 col4\" >636,025</td>\n",
       "                        <td id=\"T_ea594_row0_col5\" class=\"data row0 col5\" >9,601</td>\n",
       "                        <td id=\"T_ea594_row0_col6\" class=\"data row0 col6\" >207,849,243</td>\n",
       "                        <td id=\"T_ea594_row0_col7\" class=\"data row0 col7\" >4,366,247</td>\n",
       "                        <td id=\"T_ea594_row0_col8\" class=\"data row0 col8\" >26,809</td>\n",
       "                        <td id=\"T_ea594_row0_col9\" class=\"data row0 col9\" >563</td>\n",
       "                        <td id=\"T_ea594_row0_col10\" class=\"data row0 col10\" >2.10%</td>\n",
       "                        <td id=\"T_ea594_row0_col11\" class=\"data row0 col11\" >1.64%</td>\n",
       "                        <td id=\"T_ea594_row0_col12\" class=\"data row0 col12\" >2.21%</td>\n",
       "                        <td id=\"T_ea594_row0_col13\" class=\"data row0 col13\" >32</td>\n",
       "                        <td id=\"T_ea594_row0_col14\" class=\"data row0 col14\" >1.57%</td>\n",
       "                        <td id=\"T_ea594_row0_col15\" class=\"data row0 col15\" >45</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea594_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_ea594_row1_col0\" class=\"data row1 col0\" >America</td>\n",
       "                        <td id=\"T_ea594_row1_col1\" class=\"data row1 col1\" >77</td>\n",
       "                        <td id=\"T_ea594_row1_col2\" class=\"data row1 col2\" >1,506,128</td>\n",
       "                        <td id=\"T_ea594_row1_col3\" class=\"data row1 col3\" >19,776</td>\n",
       "                        <td id=\"T_ea594_row1_col4\" class=\"data row1 col4\" >215,161</td>\n",
       "                        <td id=\"T_ea594_row1_col5\" class=\"data row1 col5\" >2,825</td>\n",
       "                        <td id=\"T_ea594_row1_col6\" class=\"data row1 col6\" >80,476,635</td>\n",
       "                        <td id=\"T_ea594_row1_col7\" class=\"data row1 col7\" >2,059,051</td>\n",
       "                        <td id=\"T_ea594_row1_col8\" class=\"data row1 col8\" >78,767</td>\n",
       "                        <td id=\"T_ea594_row1_col9\" class=\"data row1 col9\" >2,015</td>\n",
       "                        <td id=\"T_ea594_row1_col10\" class=\"data row1 col10\" >2.56%</td>\n",
       "                        <td id=\"T_ea594_row1_col11\" class=\"data row1 col11\" >1.61%</td>\n",
       "                        <td id=\"T_ea594_row1_col12\" class=\"data row1 col12\" >1.86%</td>\n",
       "                        <td id=\"T_ea594_row1_col13\" class=\"data row1 col13\" >38</td>\n",
       "                        <td id=\"T_ea594_row1_col14\" class=\"data row1 col14\" >0.98%</td>\n",
       "                        <td id=\"T_ea594_row1_col15\" class=\"data row1 col15\" >71</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea594_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_ea594_row2_col0\" class=\"data row2 col0\" >Europe</td>\n",
       "                        <td id=\"T_ea594_row2_col1\" class=\"data row2 col1\" >78</td>\n",
       "                        <td id=\"T_ea594_row2_col2\" class=\"data row2 col2\" >1,087,120</td>\n",
       "                        <td id=\"T_ea594_row2_col3\" class=\"data row2 col3\" >9,892</td>\n",
       "                        <td id=\"T_ea594_row2_col4\" class=\"data row2 col4\" >155,303</td>\n",
       "                        <td id=\"T_ea594_row2_col5\" class=\"data row2 col5\" >1,413</td>\n",
       "                        <td id=\"T_ea594_row2_col6\" class=\"data row2 col6\" >61,095,579</td>\n",
       "                        <td id=\"T_ea594_row2_col7\" class=\"data row2 col7\" >1,221,930</td>\n",
       "                        <td id=\"T_ea594_row2_col8\" class=\"data row2 col8\" >71,776</td>\n",
       "                        <td id=\"T_ea594_row2_col9\" class=\"data row2 col9\" >1,436</td>\n",
       "                        <td id=\"T_ea594_row2_col10\" class=\"data row2 col10\" >2.00%</td>\n",
       "                        <td id=\"T_ea594_row2_col11\" class=\"data row2 col11\" >0.97%</td>\n",
       "                        <td id=\"T_ea594_row2_col12\" class=\"data row2 col12\" >1.77%</td>\n",
       "                        <td id=\"T_ea594_row2_col13\" class=\"data row2 col13\" >39</td>\n",
       "                        <td id=\"T_ea594_row2_col14\" class=\"data row2 col14\" >0.75%</td>\n",
       "                        <td id=\"T_ea594_row2_col15\" class=\"data row2 col15\" >93</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea594_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_ea594_row3_col0\" class=\"data row3 col0\" >Asia</td>\n",
       "                        <td id=\"T_ea594_row3_col1\" class=\"data row3 col1\" >83</td>\n",
       "                        <td id=\"T_ea594_row3_col2\" class=\"data row3 col2\" >1,595,514</td>\n",
       "                        <td id=\"T_ea594_row3_col3\" class=\"data row3 col3\" >31,225</td>\n",
       "                        <td id=\"T_ea594_row3_col4\" class=\"data row3 col4\" >227,931</td>\n",
       "                        <td id=\"T_ea594_row3_col5\" class=\"data row3 col5\" >4,461</td>\n",
       "                        <td id=\"T_ea594_row3_col6\" class=\"data row3 col6\" >58,844,653</td>\n",
       "                        <td id=\"T_ea594_row3_col7\" class=\"data row3 col7\" >899,568</td>\n",
       "                        <td id=\"T_ea594_row3_col8\" class=\"data row3 col8\" >13,081</td>\n",
       "                        <td id=\"T_ea594_row3_col9\" class=\"data row3 col9\" >200</td>\n",
       "                        <td id=\"T_ea594_row3_col10\" class=\"data row3 col10\" >1.53%</td>\n",
       "                        <td id=\"T_ea594_row3_col11\" class=\"data row3 col11\" >1.98%</td>\n",
       "                        <td id=\"T_ea594_row3_col12\" class=\"data row3 col12\" >2.93%</td>\n",
       "                        <td id=\"T_ea594_row3_col13\" class=\"data row3 col13\" >24</td>\n",
       "                        <td id=\"T_ea594_row3_col14\" class=\"data row3 col14\" >3.69%</td>\n",
       "                        <td id=\"T_ea594_row3_col15\" class=\"data row3 col15\" >19</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea594_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_ea594_row4_col0\" class=\"data row4 col0\" >Africa</td>\n",
       "                        <td id=\"T_ea594_row4_col1\" class=\"data row4 col1\" >75</td>\n",
       "                        <td id=\"T_ea594_row4_col2\" class=\"data row4 col2\" >248,654</td>\n",
       "                        <td id=\"T_ea594_row4_col3\" class=\"data row4 col3\" >6,140</td>\n",
       "                        <td id=\"T_ea594_row4_col4\" class=\"data row4 col4\" >35,522</td>\n",
       "                        <td id=\"T_ea594_row4_col5\" class=\"data row4 col5\" >877</td>\n",
       "                        <td id=\"T_ea594_row4_col6\" class=\"data row4 col6\" >7,292,058</td>\n",
       "                        <td id=\"T_ea594_row4_col7\" class=\"data row4 col7\" >183,766</td>\n",
       "                        <td id=\"T_ea594_row4_col8\" class=\"data row4 col8\" >5,444</td>\n",
       "                        <td id=\"T_ea594_row4_col9\" class=\"data row4 col9\" >137</td>\n",
       "                        <td id=\"T_ea594_row4_col10\" class=\"data row4 col10\" >2.52%</td>\n",
       "                        <td id=\"T_ea594_row4_col11\" class=\"data row4 col11\" >2.27%</td>\n",
       "                        <td id=\"T_ea594_row4_col12\" class=\"data row4 col12\" >3.90%</td>\n",
       "                        <td id=\"T_ea594_row4_col13\" class=\"data row4 col13\" >18</td>\n",
       "                        <td id=\"T_ea594_row4_col14\" class=\"data row4 col14\" >3.59%</td>\n",
       "                        <td id=\"T_ea594_row4_col15\" class=\"data row4 col15\" >20</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ea594_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_ea594_row5_col0\" class=\"data row5 col0\" >Oceania</td>\n",
       "                        <td id=\"T_ea594_row5_col1\" class=\"data row5 col1\" >75</td>\n",
       "                        <td id=\"T_ea594_row5_col2\" class=\"data row5 col2\" >14,757</td>\n",
       "                        <td id=\"T_ea594_row5_col3\" class=\"data row5 col3\" >171</td>\n",
       "                        <td id=\"T_ea594_row5_col4\" class=\"data row5 col4\" >2,108</td>\n",
       "                        <td id=\"T_ea594_row5_col5\" class=\"data row5 col5\" >24</td>\n",
       "                        <td id=\"T_ea594_row5_col6\" class=\"data row5 col6\" >140,318</td>\n",
       "                        <td id=\"T_ea594_row5_col7\" class=\"data row5 col7\" >1,932</td>\n",
       "                        <td id=\"T_ea594_row5_col8\" class=\"data row5 col8\" >3,330</td>\n",
       "                        <td id=\"T_ea594_row5_col9\" class=\"data row5 col9\" >46</td>\n",
       "                        <td id=\"T_ea594_row5_col10\" class=\"data row5 col10\" >1.38%</td>\n",
       "                        <td id=\"T_ea594_row5_col11\" class=\"data row5 col11\" >1.41%</td>\n",
       "                        <td id=\"T_ea594_row5_col12\" class=\"data row5 col12\" >10.53%</td>\n",
       "                        <td id=\"T_ea594_row5_col13\" class=\"data row5 col13\" >7</td>\n",
       "                        <td id=\"T_ea594_row5_col14\" class=\"data row5 col14\" >7.02%</td>\n",
       "                        <td id=\"T_ea594_row5_col15\" class=\"data row5 col15\" >10</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc43ed59410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_show(df_continents, 'Statistics by continent for: ' + asof, asof, 'cum_deaths',\n",
    "         hide_cols=['population', 'week', 'cid', 'continent'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics by country for: 2021-32 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_517e1_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >country</th>        <th class=\"col_heading level0 col1\" >timeline</th>        <th class=\"col_heading level0 col2\" >cases</th>        <th class=\"col_heading level0 col3\" >deaths</th>        <th class=\"col_heading level0 col4\" >daily_cases</th>        <th class=\"col_heading level0 col5\" >daily_deaths</th>        <th class=\"col_heading level0 col6\" >cum_cases</th>        <th class=\"col_heading level0 col7\" >cum_deaths</th>        <th class=\"col_heading level0 col8\" >pm_cases</th>        <th class=\"col_heading level0 col9\" >pm_deaths</th>        <th class=\"col_heading level0 col10\" >fatality</th>        <th class=\"col_heading level0 col11\" >fr_spot</th>        <th class=\"col_heading level0 col12\" >gr_cases</th>        <th class=\"col_heading level0 col13\" >dbl_cases</th>        <th class=\"col_heading level0 col14\" >gr_deaths</th>        <th class=\"col_heading level0 col15\" >dbl_deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_517e1_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_517e1_row0_col0\" class=\"data row0 col0\" >World</td>\n",
       "                        <td id=\"T_517e1_row0_col1\" class=\"data row0 col1\" >83</td>\n",
       "                        <td id=\"T_517e1_row0_col2\" class=\"data row0 col2\" >4,452,173</td>\n",
       "                        <td id=\"T_517e1_row0_col3\" class=\"data row0 col3\" >67,204</td>\n",
       "                        <td id=\"T_517e1_row0_col4\" class=\"data row0 col4\" >636,025</td>\n",
       "                        <td id=\"T_517e1_row0_col5\" class=\"data row0 col5\" >9,601</td>\n",
       "                        <td id=\"T_517e1_row0_col6\" class=\"data row0 col6\" >207,849,243</td>\n",
       "                        <td id=\"T_517e1_row0_col7\" class=\"data row0 col7\" >4,366,247</td>\n",
       "                        <td id=\"T_517e1_row0_col8\" class=\"data row0 col8\" >26,809</td>\n",
       "                        <td id=\"T_517e1_row0_col9\" class=\"data row0 col9\" >563</td>\n",
       "                        <td id=\"T_517e1_row0_col10\" class=\"data row0 col10\" >2.10%</td>\n",
       "                        <td id=\"T_517e1_row0_col11\" class=\"data row0 col11\" >1.64%</td>\n",
       "                        <td id=\"T_517e1_row0_col12\" class=\"data row0 col12\" >2.21%</td>\n",
       "                        <td id=\"T_517e1_row0_col13\" class=\"data row0 col13\" >32</td>\n",
       "                        <td id=\"T_517e1_row0_col14\" class=\"data row0 col14\" >1.57%</td>\n",
       "                        <td id=\"T_517e1_row0_col15\" class=\"data row0 col15\" >45</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_517e1_row1_col0\" class=\"data row1 col0\" >United States Of America</td>\n",
       "                        <td id=\"T_517e1_row1_col1\" class=\"data row1 col1\" >76</td>\n",
       "                        <td id=\"T_517e1_row1_col2\" class=\"data row1 col2\" >916,459</td>\n",
       "                        <td id=\"T_517e1_row1_col3\" class=\"data row1 col3\" >4,807</td>\n",
       "                        <td id=\"T_517e1_row1_col4\" class=\"data row1 col4\" >130,923</td>\n",
       "                        <td id=\"T_517e1_row1_col5\" class=\"data row1 col5\" >687</td>\n",
       "                        <td id=\"T_517e1_row1_col6\" class=\"data row1 col6\" >36,681,559</td>\n",
       "                        <td id=\"T_517e1_row1_col7\" class=\"data row1 col7\" >621,636</td>\n",
       "                        <td id=\"T_517e1_row1_col8\" class=\"data row1 col8\" >110,820</td>\n",
       "                        <td id=\"T_517e1_row1_col9\" class=\"data row1 col9\" >1,878</td>\n",
       "                        <td id=\"T_517e1_row1_col10\" class=\"data row1 col10\" >1.69%</td>\n",
       "                        <td id=\"T_517e1_row1_col11\" class=\"data row1 col11\" >0.86%</td>\n",
       "                        <td id=\"T_517e1_row1_col12\" class=\"data row1 col12\" >2.37%</td>\n",
       "                        <td id=\"T_517e1_row1_col13\" class=\"data row1 col13\" >30</td>\n",
       "                        <td id=\"T_517e1_row1_col14\" class=\"data row1 col14\" >0.68%</td>\n",
       "                        <td id=\"T_517e1_row1_col15\" class=\"data row1 col15\" >102</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_517e1_row2_col0\" class=\"data row2 col0\" >Brazil</td>\n",
       "                        <td id=\"T_517e1_row2_col1\" class=\"data row2 col1\" >75</td>\n",
       "                        <td id=\"T_517e1_row2_col2\" class=\"data row2 col2\" >198,427</td>\n",
       "                        <td id=\"T_517e1_row2_col3\" class=\"data row2 col3\" >5,907</td>\n",
       "                        <td id=\"T_517e1_row2_col4\" class=\"data row2 col4\" >28,347</td>\n",
       "                        <td id=\"T_517e1_row2_col5\" class=\"data row2 col5\" >844</td>\n",
       "                        <td id=\"T_517e1_row2_col6\" class=\"data row2 col6\" >20,364,099</td>\n",
       "                        <td id=\"T_517e1_row2_col7\" class=\"data row2 col7\" >569,058</td>\n",
       "                        <td id=\"T_517e1_row2_col8\" class=\"data row2 col8\" >95,804</td>\n",
       "                        <td id=\"T_517e1_row2_col9\" class=\"data row2 col9\" >2,677</td>\n",
       "                        <td id=\"T_517e1_row2_col10\" class=\"data row2 col10\" >2.79%</td>\n",
       "                        <td id=\"T_517e1_row2_col11\" class=\"data row2 col11\" >2.37%</td>\n",
       "                        <td id=\"T_517e1_row2_col12\" class=\"data row2 col12\" >1.06%</td>\n",
       "                        <td id=\"T_517e1_row2_col13\" class=\"data row2 col13\" >66</td>\n",
       "                        <td id=\"T_517e1_row2_col14\" class=\"data row2 col14\" >1.09%</td>\n",
       "                        <td id=\"T_517e1_row2_col15\" class=\"data row2 col15\" >64</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_517e1_row3_col0\" class=\"data row3 col0\" >India</td>\n",
       "                        <td id=\"T_517e1_row3_col1\" class=\"data row3 col1\" >74</td>\n",
       "                        <td id=\"T_517e1_row3_col2\" class=\"data row3 col2\" >255,559</td>\n",
       "                        <td id=\"T_517e1_row3_col3\" class=\"data row3 col3\" >3,333</td>\n",
       "                        <td id=\"T_517e1_row3_col4\" class=\"data row3 col4\" >36,508</td>\n",
       "                        <td id=\"T_517e1_row3_col5\" class=\"data row3 col5\" >476</td>\n",
       "                        <td id=\"T_517e1_row3_col6\" class=\"data row3 col6\" >32,225,513</td>\n",
       "                        <td id=\"T_517e1_row3_col7\" class=\"data row3 col7\" >431,642</td>\n",
       "                        <td id=\"T_517e1_row3_col8\" class=\"data row3 col8\" >23,352</td>\n",
       "                        <td id=\"T_517e1_row3_col9\" class=\"data row3 col9\" >313</td>\n",
       "                        <td id=\"T_517e1_row3_col10\" class=\"data row3 col10\" >1.34%</td>\n",
       "                        <td id=\"T_517e1_row3_col11\" class=\"data row3 col11\" >1.17%</td>\n",
       "                        <td id=\"T_517e1_row3_col12\" class=\"data row3 col12\" >0.83%</td>\n",
       "                        <td id=\"T_517e1_row3_col13\" class=\"data row3 col13\" >84</td>\n",
       "                        <td id=\"T_517e1_row3_col14\" class=\"data row3 col14\" >0.81%</td>\n",
       "                        <td id=\"T_517e1_row3_col15\" class=\"data row3 col15\" >86</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_517e1_row4_col0\" class=\"data row4 col0\" >Russia</td>\n",
       "                        <td id=\"T_517e1_row4_col1\" class=\"data row4 col1\" >74</td>\n",
       "                        <td id=\"T_517e1_row4_col2\" class=\"data row4 col2\" >153,086</td>\n",
       "                        <td id=\"T_517e1_row4_col3\" class=\"data row4 col3\" >5,618</td>\n",
       "                        <td id=\"T_517e1_row4_col4\" class=\"data row4 col4\" >21,869</td>\n",
       "                        <td id=\"T_517e1_row4_col5\" class=\"data row4 col5\" >803</td>\n",
       "                        <td id=\"T_517e1_row4_col6\" class=\"data row4 col6\" >6,600,836</td>\n",
       "                        <td id=\"T_517e1_row4_col7\" class=\"data row4 col7\" >170,499</td>\n",
       "                        <td id=\"T_517e1_row4_col8\" class=\"data row4 col8\" >45,232</td>\n",
       "                        <td id=\"T_517e1_row4_col9\" class=\"data row4 col9\" >1,168</td>\n",
       "                        <td id=\"T_517e1_row4_col10\" class=\"data row4 col10\" >2.58%</td>\n",
       "                        <td id=\"T_517e1_row4_col11\" class=\"data row4 col11\" >3.46%</td>\n",
       "                        <td id=\"T_517e1_row4_col12\" class=\"data row4 col12\" >2.26%</td>\n",
       "                        <td id=\"T_517e1_row4_col13\" class=\"data row4 col13\" >31</td>\n",
       "                        <td id=\"T_517e1_row4_col14\" class=\"data row4 col14\" >3.18%</td>\n",
       "                        <td id=\"T_517e1_row4_col15\" class=\"data row4 col15\" >22</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_517e1_row5_col0\" class=\"data row5 col0\" >United Kingdom</td>\n",
       "                        <td id=\"T_517e1_row5_col1\" class=\"data row5 col1\" >76</td>\n",
       "                        <td id=\"T_517e1_row5_col2\" class=\"data row5 col2\" >173,194</td>\n",
       "                        <td id=\"T_517e1_row5_col3\" class=\"data row5 col3\" >597</td>\n",
       "                        <td id=\"T_517e1_row5_col4\" class=\"data row5 col4\" >24,742</td>\n",
       "                        <td id=\"T_517e1_row5_col5\" class=\"data row5 col5\" >85</td>\n",
       "                        <td id=\"T_517e1_row5_col6\" class=\"data row5 col6\" >6,267,437</td>\n",
       "                        <td id=\"T_517e1_row5_col7\" class=\"data row5 col7\" >130,953</td>\n",
       "                        <td id=\"T_517e1_row5_col8\" class=\"data row5 col8\" >92,087</td>\n",
       "                        <td id=\"T_517e1_row5_col9\" class=\"data row5 col9\" >1,924</td>\n",
       "                        <td id=\"T_517e1_row5_col10\" class=\"data row5 col10\" >2.09%</td>\n",
       "                        <td id=\"T_517e1_row5_col11\" class=\"data row5 col11\" >0.33%</td>\n",
       "                        <td id=\"T_517e1_row5_col12\" class=\"data row5 col12\" >3.24%</td>\n",
       "                        <td id=\"T_517e1_row5_col13\" class=\"data row5 col13\" >22</td>\n",
       "                        <td id=\"T_517e1_row5_col14\" class=\"data row5 col14\" >0.47%</td>\n",
       "                        <td id=\"T_517e1_row5_col15\" class=\"data row5 col15\" >146</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_517e1_row6_col0\" class=\"data row6 col0\" >Italy</td>\n",
       "                        <td id=\"T_517e1_row6_col1\" class=\"data row6 col1\" >78</td>\n",
       "                        <td id=\"T_517e1_row6_col2\" class=\"data row6 col2\" >44,252</td>\n",
       "                        <td id=\"T_517e1_row6_col3\" class=\"data row6 col3\" >212</td>\n",
       "                        <td id=\"T_517e1_row6_col4\" class=\"data row6 col4\" >6,322</td>\n",
       "                        <td id=\"T_517e1_row6_col5\" class=\"data row6 col5\" >30</td>\n",
       "                        <td id=\"T_517e1_row6_col6\" class=\"data row6 col6\" >4,440,669</td>\n",
       "                        <td id=\"T_517e1_row6_col7\" class=\"data row6 col7\" >128,432</td>\n",
       "                        <td id=\"T_517e1_row6_col8\" class=\"data row6 col8\" >74,456</td>\n",
       "                        <td id=\"T_517e1_row6_col9\" class=\"data row6 col9\" >2,153</td>\n",
       "                        <td id=\"T_517e1_row6_col10\" class=\"data row6 col10\" >2.89%</td>\n",
       "                        <td id=\"T_517e1_row6_col11\" class=\"data row6 col11\" >0.56%</td>\n",
       "                        <td id=\"T_517e1_row6_col12\" class=\"data row6 col12\" >0.97%</td>\n",
       "                        <td id=\"T_517e1_row6_col13\" class=\"data row6 col13\" >71</td>\n",
       "                        <td id=\"T_517e1_row6_col14\" class=\"data row6 col14\" >0.14%</td>\n",
       "                        <td id=\"T_517e1_row6_col15\" class=\"data row6 col15\" >488</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_517e1_row7_col0\" class=\"data row7 col0\" >France</td>\n",
       "                        <td id=\"T_517e1_row7_col1\" class=\"data row7 col1\" >77</td>\n",
       "                        <td id=\"T_517e1_row7_col2\" class=\"data row7 col2\" >165,877</td>\n",
       "                        <td id=\"T_517e1_row7_col3\" class=\"data row7 col3\" >452</td>\n",
       "                        <td id=\"T_517e1_row7_col4\" class=\"data row7 col4\" >23,697</td>\n",
       "                        <td id=\"T_517e1_row7_col5\" class=\"data row7 col5\" >65</td>\n",
       "                        <td id=\"T_517e1_row7_col6\" class=\"data row7 col6\" >6,471,035</td>\n",
       "                        <td id=\"T_517e1_row7_col7\" class=\"data row7 col7\" >112,702</td>\n",
       "                        <td id=\"T_517e1_row7_col8\" class=\"data row7 col8\" >96,123</td>\n",
       "                        <td id=\"T_517e1_row7_col9\" class=\"data row7 col9\" >1,674</td>\n",
       "                        <td id=\"T_517e1_row7_col10\" class=\"data row7 col10\" >1.74%</td>\n",
       "                        <td id=\"T_517e1_row7_col11\" class=\"data row7 col11\" >0.30%</td>\n",
       "                        <td id=\"T_517e1_row7_col12\" class=\"data row7 col12\" >2.61%</td>\n",
       "                        <td id=\"T_517e1_row7_col13\" class=\"data row7 col13\" >27</td>\n",
       "                        <td id=\"T_517e1_row7_col14\" class=\"data row7 col14\" >0.35%</td>\n",
       "                        <td id=\"T_517e1_row7_col15\" class=\"data row7 col15\" >198</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_517e1_row8_col0\" class=\"data row8 col0\" >Germany</td>\n",
       "                        <td id=\"T_517e1_row8_col1\" class=\"data row8 col1\" >77</td>\n",
       "                        <td id=\"T_517e1_row8_col2\" class=\"data row8 col2\" >31,190</td>\n",
       "                        <td id=\"T_517e1_row8_col3\" class=\"data row8 col3\" >87</td>\n",
       "                        <td id=\"T_517e1_row8_col4\" class=\"data row8 col4\" >4,456</td>\n",
       "                        <td id=\"T_517e1_row8_col5\" class=\"data row8 col5\" >12</td>\n",
       "                        <td id=\"T_517e1_row8_col6\" class=\"data row8 col6\" >3,823,139</td>\n",
       "                        <td id=\"T_517e1_row8_col7\" class=\"data row8 col7\" >91,871</td>\n",
       "                        <td id=\"T_517e1_row8_col8\" class=\"data row8 col8\" >45,970</td>\n",
       "                        <td id=\"T_517e1_row8_col9\" class=\"data row8 col9\" >1,105</td>\n",
       "                        <td id=\"T_517e1_row8_col10\" class=\"data row8 col10\" >2.40%</td>\n",
       "                        <td id=\"T_517e1_row8_col11\" class=\"data row8 col11\" >0.57%</td>\n",
       "                        <td id=\"T_517e1_row8_col12\" class=\"data row8 col12\" >0.67%</td>\n",
       "                        <td id=\"T_517e1_row8_col13\" class=\"data row8 col13\" >103</td>\n",
       "                        <td id=\"T_517e1_row8_col14\" class=\"data row8 col14\" >0.12%</td>\n",
       "                        <td id=\"T_517e1_row8_col15\" class=\"data row8 col15\" >603</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_517e1_row9_col0\" class=\"data row9 col0\" >Spain</td>\n",
       "                        <td id=\"T_517e1_row9_col1\" class=\"data row9 col1\" >77</td>\n",
       "                        <td id=\"T_517e1_row9_col2\" class=\"data row9 col2\" >91,496</td>\n",
       "                        <td id=\"T_517e1_row9_col3\" class=\"data row9 col3\" >470</td>\n",
       "                        <td id=\"T_517e1_row9_col4\" class=\"data row9 col4\" >13,071</td>\n",
       "                        <td id=\"T_517e1_row9_col5\" class=\"data row9 col5\" >67</td>\n",
       "                        <td id=\"T_517e1_row9_col6\" class=\"data row9 col6\" >4,719,266</td>\n",
       "                        <td id=\"T_517e1_row9_col7\" class=\"data row9 col7\" >82,595</td>\n",
       "                        <td id=\"T_517e1_row9_col8\" class=\"data row9 col8\" >99,704</td>\n",
       "                        <td id=\"T_517e1_row9_col9\" class=\"data row9 col9\" >1,745</td>\n",
       "                        <td id=\"T_517e1_row9_col10\" class=\"data row9 col10\" >1.75%</td>\n",
       "                        <td id=\"T_517e1_row9_col11\" class=\"data row9 col11\" >0.29%</td>\n",
       "                        <td id=\"T_517e1_row9_col12\" class=\"data row9 col12\" >2.37%</td>\n",
       "                        <td id=\"T_517e1_row9_col13\" class=\"data row9 col13\" >30</td>\n",
       "                        <td id=\"T_517e1_row9_col14\" class=\"data row9 col14\" >0.58%</td>\n",
       "                        <td id=\"T_517e1_row9_col15\" class=\"data row9 col15\" >120</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row10\" class=\"row_heading level0 row10\" >11</th>\n",
       "                        <td id=\"T_517e1_row10_col0\" class=\"data row10 col0\" >Japan</td>\n",
       "                        <td id=\"T_517e1_row10_col1\" class=\"data row10 col1\" >78</td>\n",
       "                        <td id=\"T_517e1_row10_col2\" class=\"data row10 col2\" >97,086</td>\n",
       "                        <td id=\"T_517e1_row10_col3\" class=\"data row10 col3\" >120</td>\n",
       "                        <td id=\"T_517e1_row10_col4\" class=\"data row10 col4\" >13,869</td>\n",
       "                        <td id=\"T_517e1_row10_col5\" class=\"data row10 col5\" >17</td>\n",
       "                        <td id=\"T_517e1_row10_col6\" class=\"data row10 col6\" >1,128,382</td>\n",
       "                        <td id=\"T_517e1_row10_col7\" class=\"data row10 col7\" >15,400</td>\n",
       "                        <td id=\"T_517e1_row10_col8\" class=\"data row10 col8\" >8,922</td>\n",
       "                        <td id=\"T_517e1_row10_col9\" class=\"data row10 col9\" >122</td>\n",
       "                        <td id=\"T_517e1_row10_col10\" class=\"data row10 col10\" >1.36%</td>\n",
       "                        <td id=\"T_517e1_row10_col11\" class=\"data row10 col11\" >0.18%</td>\n",
       "                        <td id=\"T_517e1_row10_col12\" class=\"data row10 col12\" >9.80%</td>\n",
       "                        <td id=\"T_517e1_row10_col13\" class=\"data row10 col13\" >7</td>\n",
       "                        <td id=\"T_517e1_row10_col14\" class=\"data row10 col14\" >0.67%</td>\n",
       "                        <td id=\"T_517e1_row10_col15\" class=\"data row10 col15\" >104</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row11\" class=\"row_heading level0 row11\" >12</th>\n",
       "                        <td id=\"T_517e1_row11_col0\" class=\"data row11 col0\" >Sweden</td>\n",
       "                        <td id=\"T_517e1_row11_col1\" class=\"data row11 col1\" >76</td>\n",
       "                        <td id=\"T_517e1_row11_col2\" class=\"data row11 col2\" >5,812</td>\n",
       "                        <td id=\"T_517e1_row11_col3\" class=\"data row11 col3\" >0</td>\n",
       "                        <td id=\"T_517e1_row11_col4\" class=\"data row11 col4\" >830</td>\n",
       "                        <td id=\"T_517e1_row11_col5\" class=\"data row11 col5\" >0</td>\n",
       "                        <td id=\"T_517e1_row11_col6\" class=\"data row11 col6\" >1,111,177</td>\n",
       "                        <td id=\"T_517e1_row11_col7\" class=\"data row11 col7\" >14,659</td>\n",
       "                        <td id=\"T_517e1_row11_col8\" class=\"data row11 col8\" >107,593</td>\n",
       "                        <td id=\"T_517e1_row11_col9\" class=\"data row11 col9\" >1,419</td>\n",
       "                        <td id=\"T_517e1_row11_col10\" class=\"data row11 col10\" >1.32%</td>\n",
       "                        <td id=\"T_517e1_row11_col11\" class=\"data row11 col11\" >0.00%</td>\n",
       "                        <td id=\"T_517e1_row11_col12\" class=\"data row11 col12\" >0.47%</td>\n",
       "                        <td id=\"T_517e1_row11_col13\" class=\"data row11 col13\" >147</td>\n",
       "                        <td id=\"T_517e1_row11_col14\" class=\"data row11 col14\" >0.00%</td>\n",
       "                        <td id=\"T_517e1_row11_col15\" class=\"data row11 col15\" >20,321</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row12\" class=\"row_heading level0 row12\" >13</th>\n",
       "                        <td id=\"T_517e1_row12_col0\" class=\"data row12 col0\" >Switzerland</td>\n",
       "                        <td id=\"T_517e1_row12_col1\" class=\"data row12 col1\" >76</td>\n",
       "                        <td id=\"T_517e1_row12_col2\" class=\"data row12 col2\" >13,779</td>\n",
       "                        <td id=\"T_517e1_row12_col3\" class=\"data row12 col3\" >16</td>\n",
       "                        <td id=\"T_517e1_row12_col4\" class=\"data row12 col4\" >1,968</td>\n",
       "                        <td id=\"T_517e1_row12_col5\" class=\"data row12 col5\" >2</td>\n",
       "                        <td id=\"T_517e1_row12_col6\" class=\"data row12 col6\" >737,686</td>\n",
       "                        <td id=\"T_517e1_row12_col7\" class=\"data row12 col7\" >10,370</td>\n",
       "                        <td id=\"T_517e1_row12_col8\" class=\"data row12 col8\" >85,717</td>\n",
       "                        <td id=\"T_517e1_row12_col9\" class=\"data row12 col9\" >1,205</td>\n",
       "                        <td id=\"T_517e1_row12_col10\" class=\"data row12 col10\" >1.41%</td>\n",
       "                        <td id=\"T_517e1_row12_col11\" class=\"data row12 col11\" >0.30%</td>\n",
       "                        <td id=\"T_517e1_row12_col12\" class=\"data row12 col12\" >1.47%</td>\n",
       "                        <td id=\"T_517e1_row12_col13\" class=\"data row12 col13\" >48</td>\n",
       "                        <td id=\"T_517e1_row12_col14\" class=\"data row12 col14\" >0.12%</td>\n",
       "                        <td id=\"T_517e1_row12_col15\" class=\"data row12 col15\" >598</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row13\" class=\"row_heading level0 row13\" >14</th>\n",
       "                        <td id=\"T_517e1_row13_col0\" class=\"data row13 col0\" >China</td>\n",
       "                        <td id=\"T_517e1_row13_col1\" class=\"data row13 col1\" >83</td>\n",
       "                        <td id=\"T_517e1_row13_col2\" class=\"data row13 col2\" >624</td>\n",
       "                        <td id=\"T_517e1_row13_col3\" class=\"data row13 col3\" >0</td>\n",
       "                        <td id=\"T_517e1_row13_col4\" class=\"data row13 col4\" >89</td>\n",
       "                        <td id=\"T_517e1_row13_col5\" class=\"data row13 col5\" >0</td>\n",
       "                        <td id=\"T_517e1_row13_col6\" class=\"data row13 col6\" >106,467</td>\n",
       "                        <td id=\"T_517e1_row13_col7\" class=\"data row13 col7\" >4,848</td>\n",
       "                        <td id=\"T_517e1_row13_col8\" class=\"data row13 col8\" >74</td>\n",
       "                        <td id=\"T_517e1_row13_col9\" class=\"data row13 col9\" >3</td>\n",
       "                        <td id=\"T_517e1_row13_col10\" class=\"data row13 col10\" >4.55%</td>\n",
       "                        <td id=\"T_517e1_row13_col11\" class=\"data row13 col11\" >0.00%</td>\n",
       "                        <td id=\"T_517e1_row13_col12\" class=\"data row13 col12\" >0.70%</td>\n",
       "                        <td id=\"T_517e1_row13_col13\" class=\"data row13 col13\" >100</td>\n",
       "                        <td id=\"T_517e1_row13_col14\" class=\"data row13 col14\" >0.00%</td>\n",
       "                        <td id=\"T_517e1_row13_col15\" class=\"data row13 col15\" >0</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_517e1_level0_row14\" class=\"row_heading level0 row14\" >15</th>\n",
       "                        <td id=\"T_517e1_row14_col0\" class=\"data row14 col0\" >South Korea</td>\n",
       "                        <td id=\"T_517e1_row14_col1\" class=\"data row14 col1\" >78</td>\n",
       "                        <td id=\"T_517e1_row14_col2\" class=\"data row14 col2\" >13,033</td>\n",
       "                        <td id=\"T_517e1_row14_col3\" class=\"data row14 col3\" >42</td>\n",
       "                        <td id=\"T_517e1_row14_col4\" class=\"data row14 col4\" >1,862</td>\n",
       "                        <td id=\"T_517e1_row14_col5\" class=\"data row14 col5\" >6</td>\n",
       "                        <td id=\"T_517e1_row14_col6\" class=\"data row14 col6\" >225,481</td>\n",
       "                        <td id=\"T_517e1_row14_col7\" class=\"data row14 col7\" >2,167</td>\n",
       "                        <td id=\"T_517e1_row14_col8\" class=\"data row14 col8\" >4,398</td>\n",
       "                        <td id=\"T_517e1_row14_col9\" class=\"data row14 col9\" >42</td>\n",
       "                        <td id=\"T_517e1_row14_col10\" class=\"data row14 col10\" >0.96%</td>\n",
       "                        <td id=\"T_517e1_row14_col11\" class=\"data row14 col11\" >0.39%</td>\n",
       "                        <td id=\"T_517e1_row14_col12\" class=\"data row14 col12\" >5.91%</td>\n",
       "                        <td id=\"T_517e1_row14_col13\" class=\"data row14 col13\" >12</td>\n",
       "                        <td id=\"T_517e1_row14_col14\" class=\"data row14 col14\" >1.61%</td>\n",
       "                        <td id=\"T_517e1_row14_col15\" class=\"data row14 col15\" >43</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc43c865510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_show(df_mon, 'Statistics by country for: ' + asof, asof, 'cum_deaths',\n",
    "         hide_cols=['population', 'week', 'cid', 'continent'], show_nice_names=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Country Report\n",
    "\n",
    "Show recent history and charts for a given country (or the world 'WW')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# find country - empty string prints full list\n",
    "# lookup_country(df, 'so')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " United Kingdom (GBR), pop. 68,059,863: Last 8 weeks. Timeline: Week-76 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_36330_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >week</th>        <th class=\"col_heading level0 col1\" >timeline</th>        <th class=\"col_heading level0 col2\" >cases</th>        <th class=\"col_heading level0 col3\" >deaths</th>        <th class=\"col_heading level0 col4\" >daily_cases</th>        <th class=\"col_heading level0 col5\" >daily_deaths</th>        <th class=\"col_heading level0 col6\" >cum_cases</th>        <th class=\"col_heading level0 col7\" >cum_deaths</th>        <th class=\"col_heading level0 col8\" >pm_cases</th>        <th class=\"col_heading level0 col9\" >pm_deaths</th>        <th class=\"col_heading level0 col10\" >fatality</th>        <th class=\"col_heading level0 col11\" >fr_spot</th>        <th class=\"col_heading level0 col12\" >gr_cases</th>        <th class=\"col_heading level0 col13\" >dbl_cases</th>        <th class=\"col_heading level0 col14\" >gr_deaths</th>        <th class=\"col_heading level0 col15\" >dbl_deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_36330_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_36330_row0_col0\" class=\"data row0 col0\" >2021-32</td>\n",
       "                        <td id=\"T_36330_row0_col1\" class=\"data row0 col1\" >76</td>\n",
       "                        <td id=\"T_36330_row0_col2\" class=\"data row0 col2\" >173,194</td>\n",
       "                        <td id=\"T_36330_row0_col3\" class=\"data row0 col3\" >597</td>\n",
       "                        <td id=\"T_36330_row0_col4\" class=\"data row0 col4\" >24,742</td>\n",
       "                        <td id=\"T_36330_row0_col5\" class=\"data row0 col5\" >85</td>\n",
       "                        <td id=\"T_36330_row0_col6\" class=\"data row0 col6\" >6,267,437</td>\n",
       "                        <td id=\"T_36330_row0_col7\" class=\"data row0 col7\" >130,953</td>\n",
       "                        <td id=\"T_36330_row0_col8\" class=\"data row0 col8\" >92,087</td>\n",
       "                        <td id=\"T_36330_row0_col9\" class=\"data row0 col9\" >1,924</td>\n",
       "                        <td id=\"T_36330_row0_col10\" class=\"data row0 col10\" >2.09%</td>\n",
       "                        <td id=\"T_36330_row0_col11\" class=\"data row0 col11\" >0.33%</td>\n",
       "                        <td id=\"T_36330_row0_col12\" class=\"data row0 col12\" >3.24%</td>\n",
       "                        <td id=\"T_36330_row0_col13\" class=\"data row0 col13\" >22</td>\n",
       "                        <td id=\"T_36330_row0_col14\" class=\"data row0 col14\" >0.47%</td>\n",
       "                        <td id=\"T_36330_row0_col15\" class=\"data row0 col15\" >146</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_36330_row1_col0\" class=\"data row1 col0\" >2021-31</td>\n",
       "                        <td id=\"T_36330_row1_col1\" class=\"data row1 col1\" >75</td>\n",
       "                        <td id=\"T_36330_row1_col2\" class=\"data row1 col2\" >213,576</td>\n",
       "                        <td id=\"T_36330_row1_col3\" class=\"data row1 col3\" >637</td>\n",
       "                        <td id=\"T_36330_row1_col4\" class=\"data row1 col4\" >30,511</td>\n",
       "                        <td id=\"T_36330_row1_col5\" class=\"data row1 col5\" >91</td>\n",
       "                        <td id=\"T_36330_row1_col6\" class=\"data row1 col6\" >6,094,243</td>\n",
       "                        <td id=\"T_36330_row1_col7\" class=\"data row1 col7\" >130,356</td>\n",
       "                        <td id=\"T_36330_row1_col8\" class=\"data row1 col8\" >89,542</td>\n",
       "                        <td id=\"T_36330_row1_col9\" class=\"data row1 col9\" >1,915</td>\n",
       "                        <td id=\"T_36330_row1_col10\" class=\"data row1 col10\" >2.14%</td>\n",
       "                        <td id=\"T_36330_row1_col11\" class=\"data row1 col11\" >0.24%</td>\n",
       "                        <td id=\"T_36330_row1_col12\" class=\"data row1 col12\" >3.42%</td>\n",
       "                        <td id=\"T_36330_row1_col13\" class=\"data row1 col13\" >21</td>\n",
       "                        <td id=\"T_36330_row1_col14\" class=\"data row1 col14\" >0.46%</td>\n",
       "                        <td id=\"T_36330_row1_col15\" class=\"data row1 col15\" >150</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_36330_row2_col0\" class=\"data row2 col0\" >2021-30</td>\n",
       "                        <td id=\"T_36330_row2_col1\" class=\"data row2 col1\" >74</td>\n",
       "                        <td id=\"T_36330_row2_col2\" class=\"data row2 col2\" >182,755</td>\n",
       "                        <td id=\"T_36330_row2_col3\" class=\"data row2 col3\" >561</td>\n",
       "                        <td id=\"T_36330_row2_col4\" class=\"data row2 col4\" >26,108</td>\n",
       "                        <td id=\"T_36330_row2_col5\" class=\"data row2 col5\" >80</td>\n",
       "                        <td id=\"T_36330_row2_col6\" class=\"data row2 col6\" >5,880,667</td>\n",
       "                        <td id=\"T_36330_row2_col7\" class=\"data row2 col7\" >129,719</td>\n",
       "                        <td id=\"T_36330_row2_col8\" class=\"data row2 col8\" >86,404</td>\n",
       "                        <td id=\"T_36330_row2_col9\" class=\"data row2 col9\" >1,906</td>\n",
       "                        <td id=\"T_36330_row2_col10\" class=\"data row2 col10\" >2.21%</td>\n",
       "                        <td id=\"T_36330_row2_col11\" class=\"data row2 col11\" >0.18%</td>\n",
       "                        <td id=\"T_36330_row2_col12\" class=\"data row2 col12\" >4.03%</td>\n",
       "                        <td id=\"T_36330_row2_col13\" class=\"data row2 col13\" >18</td>\n",
       "                        <td id=\"T_36330_row2_col14\" class=\"data row2 col14\" >0.39%</td>\n",
       "                        <td id=\"T_36330_row2_col15\" class=\"data row2 col15\" >177</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_36330_row3_col0\" class=\"data row3 col0\" >2021-29</td>\n",
       "                        <td id=\"T_36330_row3_col1\" class=\"data row3 col1\" >73</td>\n",
       "                        <td id=\"T_36330_row3_col2\" class=\"data row3 col2\" >263,973</td>\n",
       "                        <td id=\"T_36330_row3_col3\" class=\"data row3 col3\" >450</td>\n",
       "                        <td id=\"T_36330_row3_col4\" class=\"data row3 col4\" >37,710</td>\n",
       "                        <td id=\"T_36330_row3_col5\" class=\"data row3 col5\" >64</td>\n",
       "                        <td id=\"T_36330_row3_col6\" class=\"data row3 col6\" >5,697,912</td>\n",
       "                        <td id=\"T_36330_row3_col7\" class=\"data row3 col7\" >129,158</td>\n",
       "                        <td id=\"T_36330_row3_col8\" class=\"data row3 col8\" >83,719</td>\n",
       "                        <td id=\"T_36330_row3_col9\" class=\"data row3 col9\" >1,898</td>\n",
       "                        <td id=\"T_36330_row3_col10\" class=\"data row3 col10\" >2.27%</td>\n",
       "                        <td id=\"T_36330_row3_col11\" class=\"data row3 col11\" >0.24%</td>\n",
       "                        <td id=\"T_36330_row3_col12\" class=\"data row3 col12\" >5.48%</td>\n",
       "                        <td id=\"T_36330_row3_col13\" class=\"data row3 col13\" >13</td>\n",
       "                        <td id=\"T_36330_row3_col14\" class=\"data row3 col14\" >0.28%</td>\n",
       "                        <td id=\"T_36330_row3_col15\" class=\"data row3 col15\" >244</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_36330_row4_col0\" class=\"data row4 col0\" >2021-28</td>\n",
       "                        <td id=\"T_36330_row4_col1\" class=\"data row4 col1\" >72</td>\n",
       "                        <td id=\"T_36330_row4_col2\" class=\"data row4 col2\" >312,694</td>\n",
       "                        <td id=\"T_36330_row4_col3\" class=\"data row4 col3\" >283</td>\n",
       "                        <td id=\"T_36330_row4_col4\" class=\"data row4 col4\" >44,671</td>\n",
       "                        <td id=\"T_36330_row4_col5\" class=\"data row4 col5\" >40</td>\n",
       "                        <td id=\"T_36330_row4_col6\" class=\"data row4 col6\" >5,433,939</td>\n",
       "                        <td id=\"T_36330_row4_col7\" class=\"data row4 col7\" >128,708</td>\n",
       "                        <td id=\"T_36330_row4_col8\" class=\"data row4 col8\" >79,841</td>\n",
       "                        <td id=\"T_36330_row4_col9\" class=\"data row4 col9\" >1,891</td>\n",
       "                        <td id=\"T_36330_row4_col10\" class=\"data row4 col10\" >2.37%</td>\n",
       "                        <td id=\"T_36330_row4_col11\" class=\"data row4 col11\" >0.14%</td>\n",
       "                        <td id=\"T_36330_row4_col12\" class=\"data row4 col12\" >4.98%</td>\n",
       "                        <td id=\"T_36330_row4_col13\" class=\"data row4 col13\" >14</td>\n",
       "                        <td id=\"T_36330_row4_col14\" class=\"data row4 col14\" >0.19%</td>\n",
       "                        <td id=\"T_36330_row4_col15\" class=\"data row4 col15\" >373</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_36330_row5_col0\" class=\"data row5 col0\" >2021-27</td>\n",
       "                        <td id=\"T_36330_row5_col1\" class=\"data row5 col1\" >71</td>\n",
       "                        <td id=\"T_36330_row5_col2\" class=\"data row5 col2\" >190,712</td>\n",
       "                        <td id=\"T_36330_row5_col3\" class=\"data row5 col3\" >194</td>\n",
       "                        <td id=\"T_36330_row5_col4\" class=\"data row5 col4\" >27,245</td>\n",
       "                        <td id=\"T_36330_row5_col5\" class=\"data row5 col5\" >28</td>\n",
       "                        <td id=\"T_36330_row5_col6\" class=\"data row5 col6\" >5,121,245</td>\n",
       "                        <td id=\"T_36330_row5_col7\" class=\"data row5 col7\" >128,425</td>\n",
       "                        <td id=\"T_36330_row5_col8\" class=\"data row5 col8\" >75,246</td>\n",
       "                        <td id=\"T_36330_row5_col9\" class=\"data row5 col9\" >1,887</td>\n",
       "                        <td id=\"T_36330_row5_col10\" class=\"data row5 col10\" >2.51%</td>\n",
       "                        <td id=\"T_36330_row5_col11\" class=\"data row5 col11\" >0.19%</td>\n",
       "                        <td id=\"T_36330_row5_col12\" class=\"data row5 col12\" >4.03%</td>\n",
       "                        <td id=\"T_36330_row5_col13\" class=\"data row5 col13\" >18</td>\n",
       "                        <td id=\"T_36330_row5_col14\" class=\"data row5 col14\" >0.13%</td>\n",
       "                        <td id=\"T_36330_row5_col15\" class=\"data row5 col15\" >547</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_36330_row6_col0\" class=\"data row6 col0\" >2021-26</td>\n",
       "                        <td id=\"T_36330_row6_col1\" class=\"data row6 col1\" >70</td>\n",
       "                        <td id=\"T_36330_row6_col2\" class=\"data row6 col2\" >198,099</td>\n",
       "                        <td id=\"T_36330_row6_col3\" class=\"data row6 col3\" >131</td>\n",
       "                        <td id=\"T_36330_row6_col4\" class=\"data row6 col4\" >28,300</td>\n",
       "                        <td id=\"T_36330_row6_col5\" class=\"data row6 col5\" >19</td>\n",
       "                        <td id=\"T_36330_row6_col6\" class=\"data row6 col6\" >4,930,533</td>\n",
       "                        <td id=\"T_36330_row6_col7\" class=\"data row6 col7\" >128,231</td>\n",
       "                        <td id=\"T_36330_row6_col8\" class=\"data row6 col8\" >72,444</td>\n",
       "                        <td id=\"T_36330_row6_col9\" class=\"data row6 col9\" >1,884</td>\n",
       "                        <td id=\"T_36330_row6_col10\" class=\"data row6 col10\" >2.60%</td>\n",
       "                        <td id=\"T_36330_row6_col11\" class=\"data row6 col11\" >0.23%</td>\n",
       "                        <td id=\"T_36330_row6_col12\" class=\"data row6 col12\" >3.19%</td>\n",
       "                        <td id=\"T_36330_row6_col13\" class=\"data row6 col13\" >22</td>\n",
       "                        <td id=\"T_36330_row6_col14\" class=\"data row6 col14\" >0.10%</td>\n",
       "                        <td id=\"T_36330_row6_col15\" class=\"data row6 col15\" >696</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_36330_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_36330_row7_col0\" class=\"data row7 col0\" >2021-25</td>\n",
       "                        <td id=\"T_36330_row7_col1\" class=\"data row7 col1\" >69</td>\n",
       "                        <td id=\"T_36330_row7_col2\" class=\"data row7 col2\" >102,394</td>\n",
       "                        <td id=\"T_36330_row7_col3\" class=\"data row7 col3\" >124</td>\n",
       "                        <td id=\"T_36330_row7_col4\" class=\"data row7 col4\" >14,628</td>\n",
       "                        <td id=\"T_36330_row7_col5\" class=\"data row7 col5\" >18</td>\n",
       "                        <td id=\"T_36330_row7_col6\" class=\"data row7 col6\" >4,732,434</td>\n",
       "                        <td id=\"T_36330_row7_col7\" class=\"data row7 col7\" >128,100</td>\n",
       "                        <td id=\"T_36330_row7_col8\" class=\"data row7 col8\" >69,533</td>\n",
       "                        <td id=\"T_36330_row7_col9\" class=\"data row7 col9\" >1,882</td>\n",
       "                        <td id=\"T_36330_row7_col10\" class=\"data row7 col10\" >2.71%</td>\n",
       "                        <td id=\"T_36330_row7_col11\" class=\"data row7 col11\" >0.22%</td>\n",
       "                        <td id=\"T_36330_row7_col12\" class=\"data row7 col12\" >1.72%</td>\n",
       "                        <td id=\"T_36330_row7_col13\" class=\"data row7 col13\" >41</td>\n",
       "                        <td id=\"T_36330_row7_col14\" class=\"data row7 col14\" >0.08%</td>\n",
       "                        <td id=\"T_36330_row7_col15\" class=\"data row7 col15\" >905</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc43be37190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x1512 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_country(df, 'GBR', history=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily Rankings\n",
    "\n",
    "Daily rankings by variable. By default, countries included iff cum_deaths > 100."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics for 2021-32 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_ae4d0_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country1</th>        <th class=\"col_heading level0 col1\" >Cid1</th>        <th class=\"col_heading level0 col2\" >Weekly Cases</th>        <th class=\"col_heading level0 col3\" >Country2</th>        <th class=\"col_heading level0 col4\" >Cid2</th>        <th class=\"col_heading level0 col5\" >Weekly Deaths</th>        <th class=\"col_heading level0 col6\" >Country3</th>        <th class=\"col_heading level0 col7\" >Cid3</th>        <th class=\"col_heading level0 col8\" >Cum. Cases</th>        <th class=\"col_heading level0 col9\" >Country4</th>        <th class=\"col_heading level0 col10\" >Cid4</th>        <th class=\"col_heading level0 col11\" >Cum. Deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_ae4d0_row0_col0\" class=\"data row0 col0\" >United States Of America</td>\n",
       "                        <td id=\"T_ae4d0_row0_col1\" class=\"data row0 col1\" >USA</td>\n",
       "                        <td id=\"T_ae4d0_row0_col2\" class=\"data row0 col2\" >916,459</td>\n",
       "                        <td id=\"T_ae4d0_row0_col3\" class=\"data row0 col3\" >Indonesia</td>\n",
       "                        <td id=\"T_ae4d0_row0_col4\" class=\"data row0 col4\" >IDN</td>\n",
       "                        <td id=\"T_ae4d0_row0_col5\" class=\"data row0 col5\" >10,492</td>\n",
       "                        <td id=\"T_ae4d0_row0_col6\" class=\"data row0 col6\" >United States Of America</td>\n",
       "                        <td id=\"T_ae4d0_row0_col7\" class=\"data row0 col7\" >USA</td>\n",
       "                        <td id=\"T_ae4d0_row0_col8\" class=\"data row0 col8\" >36,681,559</td>\n",
       "                        <td id=\"T_ae4d0_row0_col9\" class=\"data row0 col9\" >United States Of America</td>\n",
       "                        <td id=\"T_ae4d0_row0_col10\" class=\"data row0 col10\" >USA</td>\n",
       "                        <td id=\"T_ae4d0_row0_col11\" class=\"data row0 col11\" >621,636</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_ae4d0_row1_col0\" class=\"data row1 col0\" >India</td>\n",
       "                        <td id=\"T_ae4d0_row1_col1\" class=\"data row1 col1\" >IND</td>\n",
       "                        <td id=\"T_ae4d0_row1_col2\" class=\"data row1 col2\" >255,559</td>\n",
       "                        <td id=\"T_ae4d0_row1_col3\" class=\"data row1 col3\" >Brazil</td>\n",
       "                        <td id=\"T_ae4d0_row1_col4\" class=\"data row1 col4\" >BRA</td>\n",
       "                        <td id=\"T_ae4d0_row1_col5\" class=\"data row1 col5\" >5,907</td>\n",
       "                        <td id=\"T_ae4d0_row1_col6\" class=\"data row1 col6\" >India</td>\n",
       "                        <td id=\"T_ae4d0_row1_col7\" class=\"data row1 col7\" >IND</td>\n",
       "                        <td id=\"T_ae4d0_row1_col8\" class=\"data row1 col8\" >32,225,513</td>\n",
       "                        <td id=\"T_ae4d0_row1_col9\" class=\"data row1 col9\" >Brazil</td>\n",
       "                        <td id=\"T_ae4d0_row1_col10\" class=\"data row1 col10\" >BRA</td>\n",
       "                        <td id=\"T_ae4d0_row1_col11\" class=\"data row1 col11\" >569,058</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_ae4d0_row2_col0\" class=\"data row2 col0\" >Iran</td>\n",
       "                        <td id=\"T_ae4d0_row2_col1\" class=\"data row2 col1\" >IRN</td>\n",
       "                        <td id=\"T_ae4d0_row2_col2\" class=\"data row2 col2\" >230,356</td>\n",
       "                        <td id=\"T_ae4d0_row2_col3\" class=\"data row2 col3\" >Russia</td>\n",
       "                        <td id=\"T_ae4d0_row2_col4\" class=\"data row2 col4\" >RUS</td>\n",
       "                        <td id=\"T_ae4d0_row2_col5\" class=\"data row2 col5\" >5,618</td>\n",
       "                        <td id=\"T_ae4d0_row2_col6\" class=\"data row2 col6\" >Brazil</td>\n",
       "                        <td id=\"T_ae4d0_row2_col7\" class=\"data row2 col7\" >BRA</td>\n",
       "                        <td id=\"T_ae4d0_row2_col8\" class=\"data row2 col8\" >20,364,099</td>\n",
       "                        <td id=\"T_ae4d0_row2_col9\" class=\"data row2 col9\" >India</td>\n",
       "                        <td id=\"T_ae4d0_row2_col10\" class=\"data row2 col10\" >IND</td>\n",
       "                        <td id=\"T_ae4d0_row2_col11\" class=\"data row2 col11\" >431,642</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_ae4d0_row3_col0\" class=\"data row3 col0\" >Brazil</td>\n",
       "                        <td id=\"T_ae4d0_row3_col1\" class=\"data row3 col1\" >BRA</td>\n",
       "                        <td id=\"T_ae4d0_row3_col2\" class=\"data row3 col2\" >198,427</td>\n",
       "                        <td id=\"T_ae4d0_row3_col3\" class=\"data row3 col3\" >United States Of America</td>\n",
       "                        <td id=\"T_ae4d0_row3_col4\" class=\"data row3 col4\" >USA</td>\n",
       "                        <td id=\"T_ae4d0_row3_col5\" class=\"data row3 col5\" >4,807</td>\n",
       "                        <td id=\"T_ae4d0_row3_col6\" class=\"data row3 col6\" >Russia</td>\n",
       "                        <td id=\"T_ae4d0_row3_col7\" class=\"data row3 col7\" >RUS</td>\n",
       "                        <td id=\"T_ae4d0_row3_col8\" class=\"data row3 col8\" >6,600,836</td>\n",
       "                        <td id=\"T_ae4d0_row3_col9\" class=\"data row3 col9\" >Mexico</td>\n",
       "                        <td id=\"T_ae4d0_row3_col10\" class=\"data row3 col10\" >MEX</td>\n",
       "                        <td id=\"T_ae4d0_row3_col11\" class=\"data row3 col11\" >248,652</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_ae4d0_row4_col0\" class=\"data row4 col0\" >Indonesia</td>\n",
       "                        <td id=\"T_ae4d0_row4_col1\" class=\"data row4 col1\" >IDN</td>\n",
       "                        <td id=\"T_ae4d0_row4_col2\" class=\"data row4 col2\" >188,323</td>\n",
       "                        <td id=\"T_ae4d0_row4_col3\" class=\"data row4 col3\" >Mexico</td>\n",
       "                        <td id=\"T_ae4d0_row4_col4\" class=\"data row4 col4\" >MEX</td>\n",
       "                        <td id=\"T_ae4d0_row4_col5\" class=\"data row4 col5\" >3,962</td>\n",
       "                        <td id=\"T_ae4d0_row4_col6\" class=\"data row4 col6\" >France</td>\n",
       "                        <td id=\"T_ae4d0_row4_col7\" class=\"data row4 col7\" >FRA</td>\n",
       "                        <td id=\"T_ae4d0_row4_col8\" class=\"data row4 col8\" >6,471,035</td>\n",
       "                        <td id=\"T_ae4d0_row4_col9\" class=\"data row4 col9\" >Peru</td>\n",
       "                        <td id=\"T_ae4d0_row4_col10\" class=\"data row4 col10\" >PER</td>\n",
       "                        <td id=\"T_ae4d0_row4_col11\" class=\"data row4 col11\" >197,487</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_ae4d0_row5_col0\" class=\"data row5 col0\" >Turkey</td>\n",
       "                        <td id=\"T_ae4d0_row5_col1\" class=\"data row5 col1\" >TUR</td>\n",
       "                        <td id=\"T_ae4d0_row5_col2\" class=\"data row5 col2\" >187,922</td>\n",
       "                        <td id=\"T_ae4d0_row5_col3\" class=\"data row5 col3\" >India</td>\n",
       "                        <td id=\"T_ae4d0_row5_col4\" class=\"data row5 col4\" >IND</td>\n",
       "                        <td id=\"T_ae4d0_row5_col5\" class=\"data row5 col5\" >3,333</td>\n",
       "                        <td id=\"T_ae4d0_row5_col6\" class=\"data row5 col6\" >United Kingdom</td>\n",
       "                        <td id=\"T_ae4d0_row5_col7\" class=\"data row5 col7\" >GBR</td>\n",
       "                        <td id=\"T_ae4d0_row5_col8\" class=\"data row5 col8\" >6,267,437</td>\n",
       "                        <td id=\"T_ae4d0_row5_col9\" class=\"data row5 col9\" >Russia</td>\n",
       "                        <td id=\"T_ae4d0_row5_col10\" class=\"data row5 col10\" >RUS</td>\n",
       "                        <td id=\"T_ae4d0_row5_col11\" class=\"data row5 col11\" >170,499</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_ae4d0_row6_col0\" class=\"data row6 col0\" >United Kingdom</td>\n",
       "                        <td id=\"T_ae4d0_row6_col1\" class=\"data row6 col1\" >GBR</td>\n",
       "                        <td id=\"T_ae4d0_row6_col2\" class=\"data row6 col2\" >173,194</td>\n",
       "                        <td id=\"T_ae4d0_row6_col3\" class=\"data row6 col3\" >Iran</td>\n",
       "                        <td id=\"T_ae4d0_row6_col4\" class=\"data row6 col4\" >IRN</td>\n",
       "                        <td id=\"T_ae4d0_row6_col5\" class=\"data row6 col5\" >3,193</td>\n",
       "                        <td id=\"T_ae4d0_row6_col6\" class=\"data row6 col6\" >Turkey</td>\n",
       "                        <td id=\"T_ae4d0_row6_col7\" class=\"data row6 col7\" >TUR</td>\n",
       "                        <td id=\"T_ae4d0_row6_col8\" class=\"data row6 col8\" >6,059,788</td>\n",
       "                        <td id=\"T_ae4d0_row6_col9\" class=\"data row6 col9\" >United Kingdom</td>\n",
       "                        <td id=\"T_ae4d0_row6_col10\" class=\"data row6 col10\" >GBR</td>\n",
       "                        <td id=\"T_ae4d0_row6_col11\" class=\"data row6 col11\" >130,953</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_ae4d0_row7_col0\" class=\"data row7 col0\" >France</td>\n",
       "                        <td id=\"T_ae4d0_row7_col1\" class=\"data row7 col1\" >FRA</td>\n",
       "                        <td id=\"T_ae4d0_row7_col2\" class=\"data row7 col2\" >165,877</td>\n",
       "                        <td id=\"T_ae4d0_row7_col3\" class=\"data row7 col3\" >Vietnam</td>\n",
       "                        <td id=\"T_ae4d0_row7_col4\" class=\"data row7 col4\" >VNM</td>\n",
       "                        <td id=\"T_ae4d0_row7_col5\" class=\"data row7 col5\" >2,377</td>\n",
       "                        <td id=\"T_ae4d0_row7_col6\" class=\"data row7 col6\" >Argentina</td>\n",
       "                        <td id=\"T_ae4d0_row7_col7\" class=\"data row7 col7\" >ARG</td>\n",
       "                        <td id=\"T_ae4d0_row7_col8\" class=\"data row7 col8\" >5,088,259</td>\n",
       "                        <td id=\"T_ae4d0_row7_col9\" class=\"data row7 col9\" >Italy</td>\n",
       "                        <td id=\"T_ae4d0_row7_col10\" class=\"data row7 col10\" >ITA</td>\n",
       "                        <td id=\"T_ae4d0_row7_col11\" class=\"data row7 col11\" >128,432</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_ae4d0_row8_col0\" class=\"data row8 col0\" >Russia</td>\n",
       "                        <td id=\"T_ae4d0_row8_col1\" class=\"data row8 col1\" >RUS</td>\n",
       "                        <td id=\"T_ae4d0_row8_col2\" class=\"data row8 col2\" >153,086</td>\n",
       "                        <td id=\"T_ae4d0_row8_col3\" class=\"data row8 col3\" >South Africa</td>\n",
       "                        <td id=\"T_ae4d0_row8_col4\" class=\"data row8 col4\" >ZAF</td>\n",
       "                        <td id=\"T_ae4d0_row8_col5\" class=\"data row8 col5\" >2,328</td>\n",
       "                        <td id=\"T_ae4d0_row8_col6\" class=\"data row8 col6\" >Colombia</td>\n",
       "                        <td id=\"T_ae4d0_row8_col7\" class=\"data row8 col7\" >COL</td>\n",
       "                        <td id=\"T_ae4d0_row8_col8\" class=\"data row8 col8\" >4,870,877</td>\n",
       "                        <td id=\"T_ae4d0_row8_col9\" class=\"data row8 col9\" >Colombia</td>\n",
       "                        <td id=\"T_ae4d0_row8_col10\" class=\"data row8 col10\" >COL</td>\n",
       "                        <td id=\"T_ae4d0_row8_col11\" class=\"data row8 col11\" >123,580</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_ae4d0_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_ae4d0_row9_col0\" class=\"data row9 col0\" >Malaysia</td>\n",
       "                        <td id=\"T_ae4d0_row9_col1\" class=\"data row9 col1\" >MYS</td>\n",
       "                        <td id=\"T_ae4d0_row9_col2\" class=\"data row9 col2\" >142,359</td>\n",
       "                        <td id=\"T_ae4d0_row9_col3\" class=\"data row9 col3\" >Kazakhstan</td>\n",
       "                        <td id=\"T_ae4d0_row9_col4\" class=\"data row9 col4\" >KAZ</td>\n",
       "                        <td id=\"T_ae4d0_row9_col5\" class=\"data row9 col5\" >1,816</td>\n",
       "                        <td id=\"T_ae4d0_row9_col6\" class=\"data row9 col6\" >Spain</td>\n",
       "                        <td id=\"T_ae4d0_row9_col7\" class=\"data row9 col7\" >ESP</td>\n",
       "                        <td id=\"T_ae4d0_row9_col8\" class=\"data row9 col8\" >4,719,266</td>\n",
       "                        <td id=\"T_ae4d0_row9_col9\" class=\"data row9 col9\" >Indonesia</td>\n",
       "                        <td id=\"T_ae4d0_row9_col10\" class=\"data row9 col10\" >IDN</td>\n",
       "                        <td id=\"T_ae4d0_row9_col11\" class=\"data row9 col11\" >117,588</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc44132da90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_stats(df, asof, ['cases', 'deaths', 'cum_cases', 'cum_deaths'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics for 2021-32 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_c6ab8_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country1</th>        <th class=\"col_heading level0 col1\" >Cid1</th>        <th class=\"col_heading level0 col2\" >Cases (pm)</th>        <th class=\"col_heading level0 col3\" >Country2</th>        <th class=\"col_heading level0 col4\" >Cid2</th>        <th class=\"col_heading level0 col5\" >Deaths (pm)</th>        <th class=\"col_heading level0 col6\" >Country3</th>        <th class=\"col_heading level0 col7\" >Cid3</th>        <th class=\"col_heading level0 col8\" >Growth-r Cases</th>        <th class=\"col_heading level0 col9\" >Country4</th>        <th class=\"col_heading level0 col10\" >Cid4</th>        <th class=\"col_heading level0 col11\" >Growth-r Deaths</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_c6ab8_row0_col0\" class=\"data row0 col0\" >Andorra</td>\n",
       "                        <td id=\"T_c6ab8_row0_col1\" class=\"data row0 col1\" >AND</td>\n",
       "                        <td id=\"T_c6ab8_row0_col2\" class=\"data row0 col2\" >196,240</td>\n",
       "                        <td id=\"T_c6ab8_row0_col3\" class=\"data row0 col3\" >Peru</td>\n",
       "                        <td id=\"T_c6ab8_row0_col4\" class=\"data row0 col4\" >PER</td>\n",
       "                        <td id=\"T_c6ab8_row0_col5\" class=\"data row0 col5\" >5,990</td>\n",
       "                        <td id=\"T_c6ab8_row0_col6\" class=\"data row0 col6\" >Vietnam</td>\n",
       "                        <td id=\"T_c6ab8_row0_col7\" class=\"data row0 col7\" >VNM</td>\n",
       "                        <td id=\"T_c6ab8_row0_col8\" class=\"data row0 col8\" >32.15%</td>\n",
       "                        <td id=\"T_c6ab8_row0_col9\" class=\"data row0 col9\" >Vietnam</td>\n",
       "                        <td id=\"T_c6ab8_row0_col10\" class=\"data row0 col10\" >VNM</td>\n",
       "                        <td id=\"T_c6ab8_row0_col11\" class=\"data row0 col11\" >110.26%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_c6ab8_row1_col0\" class=\"data row1 col0\" >Montenegro</td>\n",
       "                        <td id=\"T_c6ab8_row1_col1\" class=\"data row1 col1\" >MNE</td>\n",
       "                        <td id=\"T_c6ab8_row1_col2\" class=\"data row1 col2\" >171,212</td>\n",
       "                        <td id=\"T_c6ab8_row1_col3\" class=\"data row1 col3\" >Hungary</td>\n",
       "                        <td id=\"T_c6ab8_row1_col4\" class=\"data row1 col4\" >HUN</td>\n",
       "                        <td id=\"T_c6ab8_row1_col5\" class=\"data row1 col5\" >3,075</td>\n",
       "                        <td id=\"T_c6ab8_row1_col6\" class=\"data row1 col6\" >French Polynesia</td>\n",
       "                        <td id=\"T_c6ab8_row1_col7\" class=\"data row1 col7\" >PYF</td>\n",
       "                        <td id=\"T_c6ab8_row1_col8\" class=\"data row1 col8\" >22.13%</td>\n",
       "                        <td id=\"T_c6ab8_row1_col9\" class=\"data row1 col9\" >Fiji</td>\n",
       "                        <td id=\"T_c6ab8_row1_col10\" class=\"data row1 col10\" >FJI</td>\n",
       "                        <td id=\"T_c6ab8_row1_col11\" class=\"data row1 col11\" >27.86%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_c6ab8_row2_col0\" class=\"data row2 col0\" >Bahrain</td>\n",
       "                        <td id=\"T_c6ab8_row2_col1\" class=\"data row2 col1\" >BHR</td>\n",
       "                        <td id=\"T_c6ab8_row2_col2\" class=\"data row2 col2\" >159,216</td>\n",
       "                        <td id=\"T_c6ab8_row2_col3\" class=\"data row2 col3\" >Bosnia And Herzegovina</td>\n",
       "                        <td id=\"T_c6ab8_row2_col4\" class=\"data row2 col4\" >BIH</td>\n",
       "                        <td id=\"T_c6ab8_row2_col5\" class=\"data row2 col5\" >2,960</td>\n",
       "                        <td id=\"T_c6ab8_row2_col6\" class=\"data row2 col6\" >Thailand</td>\n",
       "                        <td id=\"T_c6ab8_row2_col7\" class=\"data row2 col7\" >THA</td>\n",
       "                        <td id=\"T_c6ab8_row2_col8\" class=\"data row2 col8\" >19.69%</td>\n",
       "                        <td id=\"T_c6ab8_row2_col9\" class=\"data row2 col9\" >Liberia</td>\n",
       "                        <td id=\"T_c6ab8_row2_col10\" class=\"data row2 col10\" >LBR</td>\n",
       "                        <td id=\"T_c6ab8_row2_col11\" class=\"data row2 col11\" >22.20%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_c6ab8_row3_col0\" class=\"data row3 col0\" >Czechia</td>\n",
       "                        <td id=\"T_c6ab8_row3_col1\" class=\"data row3 col1\" >CZE</td>\n",
       "                        <td id=\"T_c6ab8_row3_col2\" class=\"data row3 col2\" >156,752</td>\n",
       "                        <td id=\"T_c6ab8_row3_col3\" class=\"data row3 col3\" >Czechia</td>\n",
       "                        <td id=\"T_c6ab8_row3_col4\" class=\"data row3 col4\" >CZE</td>\n",
       "                        <td id=\"T_c6ab8_row3_col5\" class=\"data row3 col5\" >2,840</td>\n",
       "                        <td id=\"T_c6ab8_row3_col6\" class=\"data row3 col6\" >Eswatini</td>\n",
       "                        <td id=\"T_c6ab8_row3_col7\" class=\"data row3 col7\" >SWZ</td>\n",
       "                        <td id=\"T_c6ab8_row3_col8\" class=\"data row3 col8\" >17.19%</td>\n",
       "                        <td id=\"T_c6ab8_row3_col9\" class=\"data row3 col9\" >Thailand</td>\n",
       "                        <td id=\"T_c6ab8_row3_col10\" class=\"data row3 col10\" >THA</td>\n",
       "                        <td id=\"T_c6ab8_row3_col11\" class=\"data row3 col11\" >20.88%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_c6ab8_row4_col0\" class=\"data row4 col0\" >Maldives</td>\n",
       "                        <td id=\"T_c6ab8_row4_col1\" class=\"data row4 col1\" >MDV</td>\n",
       "                        <td id=\"T_c6ab8_row4_col2\" class=\"data row4 col2\" >146,396</td>\n",
       "                        <td id=\"T_c6ab8_row4_col3\" class=\"data row4 col3\" >Brazil</td>\n",
       "                        <td id=\"T_c6ab8_row4_col4\" class=\"data row4 col4\" >BRA</td>\n",
       "                        <td id=\"T_c6ab8_row4_col5\" class=\"data row4 col5\" >2,677</td>\n",
       "                        <td id=\"T_c6ab8_row4_col6\" class=\"data row4 col6\" >Fiji</td>\n",
       "                        <td id=\"T_c6ab8_row4_col7\" class=\"data row4 col7\" >FJI</td>\n",
       "                        <td id=\"T_c6ab8_row4_col8\" class=\"data row4 col8\" >15.52%</td>\n",
       "                        <td id=\"T_c6ab8_row4_col9\" class=\"data row4 col9\" >Cuba</td>\n",
       "                        <td id=\"T_c6ab8_row4_col10\" class=\"data row4 col10\" >CUB</td>\n",
       "                        <td id=\"T_c6ab8_row4_col11\" class=\"data row4 col11\" >18.47%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_c6ab8_row5_col0\" class=\"data row5 col0\" >Slovakia</td>\n",
       "                        <td id=\"T_c6ab8_row5_col1\" class=\"data row5 col1\" >SVK</td>\n",
       "                        <td id=\"T_c6ab8_row5_col2\" class=\"data row5 col2\" >142,963</td>\n",
       "                        <td id=\"T_c6ab8_row5_col3\" class=\"data row5 col3\" >North Macedonia</td>\n",
       "                        <td id=\"T_c6ab8_row5_col4\" class=\"data row5 col4\" >MKD</td>\n",
       "                        <td id=\"T_c6ab8_row5_col5\" class=\"data row5 col5\" >2,674</td>\n",
       "                        <td id=\"T_c6ab8_row5_col6\" class=\"data row5 col6\" >Cuba</td>\n",
       "                        <td id=\"T_c6ab8_row5_col7\" class=\"data row5 col7\" >CUB</td>\n",
       "                        <td id=\"T_c6ab8_row5_col8\" class=\"data row5 col8\" >14.25%</td>\n",
       "                        <td id=\"T_c6ab8_row5_col9\" class=\"data row5 col9\" >French Polynesia</td>\n",
       "                        <td id=\"T_c6ab8_row5_col10\" class=\"data row5 col10\" >PYF</td>\n",
       "                        <td id=\"T_c6ab8_row5_col11\" class=\"data row5 col11\" >17.43%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_c6ab8_row6_col0\" class=\"data row6 col0\" >Aruba</td>\n",
       "                        <td id=\"T_c6ab8_row6_col1\" class=\"data row6 col1\" >ABW</td>\n",
       "                        <td id=\"T_c6ab8_row6_col2\" class=\"data row6 col2\" >125,096</td>\n",
       "                        <td id=\"T_c6ab8_row6_col3\" class=\"data row6 col3\" >Montenegro</td>\n",
       "                        <td id=\"T_c6ab8_row6_col4\" class=\"data row6 col4\" >MNE</td>\n",
       "                        <td id=\"T_c6ab8_row6_col5\" class=\"data row6 col5\" >2,647</td>\n",
       "                        <td id=\"T_c6ab8_row6_col6\" class=\"data row6 col6\" >Botswana</td>\n",
       "                        <td id=\"T_c6ab8_row6_col7\" class=\"data row6 col7\" >BWA</td>\n",
       "                        <td id=\"T_c6ab8_row6_col8\" class=\"data row6 col8\" >13.22%</td>\n",
       "                        <td id=\"T_c6ab8_row6_col9\" class=\"data row6 col9\" >Myanmar</td>\n",
       "                        <td id=\"T_c6ab8_row6_col10\" class=\"data row6 col10\" >MMR</td>\n",
       "                        <td id=\"T_c6ab8_row6_col11\" class=\"data row6 col11\" >16.75%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_c6ab8_row7_col0\" class=\"data row7 col0\" >Slovenia</td>\n",
       "                        <td id=\"T_c6ab8_row7_col1\" class=\"data row7 col1\" >SVN</td>\n",
       "                        <td id=\"T_c6ab8_row7_col2\" class=\"data row7 col2\" >124,907</td>\n",
       "                        <td id=\"T_c6ab8_row7_col3\" class=\"data row7 col3\" >Bulgaria</td>\n",
       "                        <td id=\"T_c6ab8_row7_col4\" class=\"data row7 col4\" >BGR</td>\n",
       "                        <td id=\"T_c6ab8_row7_col5\" class=\"data row7 col5\" >2,639</td>\n",
       "                        <td id=\"T_c6ab8_row7_col6\" class=\"data row7 col6\" >Malaysia</td>\n",
       "                        <td id=\"T_c6ab8_row7_col7\" class=\"data row7 col7\" >MYS</td>\n",
       "                        <td id=\"T_c6ab8_row7_col8\" class=\"data row7 col8\" >11.48%</td>\n",
       "                        <td id=\"T_c6ab8_row7_col9\" class=\"data row7 col9\" >Malaysia</td>\n",
       "                        <td id=\"T_c6ab8_row7_col10\" class=\"data row7 col10\" >MYS</td>\n",
       "                        <td id=\"T_c6ab8_row7_col11\" class=\"data row7 col11\" >16.71%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_c6ab8_row8_col0\" class=\"data row8 col0\" >Cyprus</td>\n",
       "                        <td id=\"T_c6ab8_row8_col1\" class=\"data row8 col1\" >CYP</td>\n",
       "                        <td id=\"T_c6ab8_row8_col2\" class=\"data row8 col2\" >122,569</td>\n",
       "                        <td id=\"T_c6ab8_row8_col3\" class=\"data row8 col3\" >Colombia</td>\n",
       "                        <td id=\"T_c6ab8_row8_col4\" class=\"data row8 col4\" >COL</td>\n",
       "                        <td id=\"T_c6ab8_row8_col5\" class=\"data row8 col5\" >2,429</td>\n",
       "                        <td id=\"T_c6ab8_row8_col6\" class=\"data row8 col6\" >Morocco</td>\n",
       "                        <td id=\"T_c6ab8_row8_col7\" class=\"data row8 col7\" >MAR</td>\n",
       "                        <td id=\"T_c6ab8_row8_col8\" class=\"data row8 col8\" >9.82%</td>\n",
       "                        <td id=\"T_c6ab8_row8_col9\" class=\"data row8 col9\" >Kazakhstan</td>\n",
       "                        <td id=\"T_c6ab8_row8_col10\" class=\"data row8 col10\" >KAZ</td>\n",
       "                        <td id=\"T_c6ab8_row8_col11\" class=\"data row8 col11\" >13.65%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_c6ab8_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_c6ab8_row9_col0\" class=\"data row9 col0\" >Georgia</td>\n",
       "                        <td id=\"T_c6ab8_row9_col1\" class=\"data row9 col1\" >GEO</td>\n",
       "                        <td id=\"T_c6ab8_row9_col2\" class=\"data row9 col2\" >120,721</td>\n",
       "                        <td id=\"T_c6ab8_row9_col3\" class=\"data row9 col3\" >Argentina</td>\n",
       "                        <td id=\"T_c6ab8_row9_col4\" class=\"data row9 col4\" >ARG</td>\n",
       "                        <td id=\"T_c6ab8_row9_col5\" class=\"data row9 col5\" >2,414</td>\n",
       "                        <td id=\"T_c6ab8_row9_col6\" class=\"data row9 col6\" >Japan</td>\n",
       "                        <td id=\"T_c6ab8_row9_col7\" class=\"data row9 col7\" >JPN</td>\n",
       "                        <td id=\"T_c6ab8_row9_col8\" class=\"data row9 col8\" >9.80%</td>\n",
       "                        <td id=\"T_c6ab8_row9_col9\" class=\"data row9 col9\" >Mongolia</td>\n",
       "                        <td id=\"T_c6ab8_row9_col10\" class=\"data row9 col10\" >MNG</td>\n",
       "                        <td id=\"T_c6ab8_row9_col11\" class=\"data row9 col11\" >13.54%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc44133d250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_stats(df, asof, ['pm_cases', 'pm_deaths', 'gr_cases', 'gr_deaths'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Statistics for 2021-32 \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_1100f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Country1</th>        <th class=\"col_heading level0 col1\" >Cid1</th>        <th class=\"col_heading level0 col2\" >Fatality</th>        <th class=\"col_heading level0 col3\" >Country2</th>        <th class=\"col_heading level0 col4\" >Cid2</th>        <th class=\"col_heading level0 col5\" >Fatality (spot)</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_1100f_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
       "                        <td id=\"T_1100f_row0_col0\" class=\"data row0 col0\" >Yemen</td>\n",
       "                        <td id=\"T_1100f_row0_col1\" class=\"data row0 col1\" >YEM</td>\n",
       "                        <td id=\"T_1100f_row0_col2\" class=\"data row0 col2\" >19.24%</td>\n",
       "                        <td id=\"T_1100f_row0_col3\" class=\"data row0 col3\" >Yemen</td>\n",
       "                        <td id=\"T_1100f_row0_col4\" class=\"data row0 col4\" >YEM</td>\n",
       "                        <td id=\"T_1100f_row0_col5\" class=\"data row0 col5\" >29.31%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
       "                        <td id=\"T_1100f_row1_col0\" class=\"data row1 col0\" >Peru</td>\n",
       "                        <td id=\"T_1100f_row1_col1\" class=\"data row1 col1\" >PER</td>\n",
       "                        <td id=\"T_1100f_row1_col2\" class=\"data row1 col2\" >9.25%</td>\n",
       "                        <td id=\"T_1100f_row1_col3\" class=\"data row1 col3\" >Somalia</td>\n",
       "                        <td id=\"T_1100f_row1_col4\" class=\"data row1 col4\" >SOM</td>\n",
       "                        <td id=\"T_1100f_row1_col5\" class=\"data row1 col5\" >18.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
       "                        <td id=\"T_1100f_row2_col0\" class=\"data row2 col0\" >Mexico</td>\n",
       "                        <td id=\"T_1100f_row2_col1\" class=\"data row2 col1\" >MEX</td>\n",
       "                        <td id=\"T_1100f_row2_col2\" class=\"data row2 col2\" >8.00%</td>\n",
       "                        <td id=\"T_1100f_row2_col3\" class=\"data row2 col3\" >Syria</td>\n",
       "                        <td id=\"T_1100f_row2_col4\" class=\"data row2 col4\" >SYR</td>\n",
       "                        <td id=\"T_1100f_row2_col5\" class=\"data row2 col5\" >16.04%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
       "                        <td id=\"T_1100f_row3_col0\" class=\"data row3 col0\" >Sudan</td>\n",
       "                        <td id=\"T_1100f_row3_col1\" class=\"data row3 col1\" >SDN</td>\n",
       "                        <td id=\"T_1100f_row3_col2\" class=\"data row3 col2\" >7.40%</td>\n",
       "                        <td id=\"T_1100f_row3_col3\" class=\"data row3 col3\" >Egypt</td>\n",
       "                        <td id=\"T_1100f_row3_col4\" class=\"data row3 col4\" >EGY</td>\n",
       "                        <td id=\"T_1100f_row3_col5\" class=\"data row3 col5\" >15.33%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
       "                        <td id=\"T_1100f_row4_col0\" class=\"data row4 col0\" >Syria</td>\n",
       "                        <td id=\"T_1100f_row4_col1\" class=\"data row4 col1\" >SYR</td>\n",
       "                        <td id=\"T_1100f_row4_col2\" class=\"data row4 col2\" >7.35%</td>\n",
       "                        <td id=\"T_1100f_row4_col3\" class=\"data row4 col3\" >North Macedonia</td>\n",
       "                        <td id=\"T_1100f_row4_col4\" class=\"data row4 col4\" >MKD</td>\n",
       "                        <td id=\"T_1100f_row4_col5\" class=\"data row4 col5\" >12.30%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
       "                        <td id=\"T_1100f_row5_col0\" class=\"data row5 col0\" >Ecuador</td>\n",
       "                        <td id=\"T_1100f_row5_col1\" class=\"data row5 col1\" >ECU</td>\n",
       "                        <td id=\"T_1100f_row5_col2\" class=\"data row5 col2\" >6.45%</td>\n",
       "                        <td id=\"T_1100f_row5_col3\" class=\"data row5 col3\" >Taiwan</td>\n",
       "                        <td id=\"T_1100f_row5_col4\" class=\"data row5 col4\" >TWN</td>\n",
       "                        <td id=\"T_1100f_row5_col5\" class=\"data row5 col5\" >6.11%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
       "                        <td id=\"T_1100f_row6_col0\" class=\"data row6 col0\" >Egypt</td>\n",
       "                        <td id=\"T_1100f_row6_col1\" class=\"data row6 col1\" >EGY</td>\n",
       "                        <td id=\"T_1100f_row6_col2\" class=\"data row6 col2\" >5.82%</td>\n",
       "                        <td id=\"T_1100f_row6_col3\" class=\"data row6 col3\" >Bulgaria</td>\n",
       "                        <td id=\"T_1100f_row6_col4\" class=\"data row6 col4\" >BGR</td>\n",
       "                        <td id=\"T_1100f_row6_col5\" class=\"data row6 col5\" >6.09%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
       "                        <td id=\"T_1100f_row7_col0\" class=\"data row7 col0\" >Somalia</td>\n",
       "                        <td id=\"T_1100f_row7_col1\" class=\"data row7 col1\" >SOM</td>\n",
       "                        <td id=\"T_1100f_row7_col2\" class=\"data row7 col2\" >5.40%</td>\n",
       "                        <td id=\"T_1100f_row7_col3\" class=\"data row7 col3\" >Jamaica</td>\n",
       "                        <td id=\"T_1100f_row7_col4\" class=\"data row7 col4\" >JAM</td>\n",
       "                        <td id=\"T_1100f_row7_col5\" class=\"data row7 col5\" >5.97%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
       "                        <td id=\"T_1100f_row8_col0\" class=\"data row8 col0\" >Taiwan</td>\n",
       "                        <td id=\"T_1100f_row8_col1\" class=\"data row8 col1\" >TWN</td>\n",
       "                        <td id=\"T_1100f_row8_col2\" class=\"data row8 col2\" >5.18%</td>\n",
       "                        <td id=\"T_1100f_row8_col3\" class=\"data row8 col3\" >Bosnia And Herzegovina</td>\n",
       "                        <td id=\"T_1100f_row8_col4\" class=\"data row8 col4\" >BIH</td>\n",
       "                        <td id=\"T_1100f_row8_col5\" class=\"data row8 col5\" >5.61%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_1100f_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
       "                        <td id=\"T_1100f_row9_col0\" class=\"data row9 col0\" >Bosnia And Herzegovina</td>\n",
       "                        <td id=\"T_1100f_row9_col1\" class=\"data row9 col1\" >BIH</td>\n",
       "                        <td id=\"T_1100f_row9_col2\" class=\"data row9 col2\" >4.68%</td>\n",
       "                        <td id=\"T_1100f_row9_col3\" class=\"data row9 col3\" >Angola</td>\n",
       "                        <td id=\"T_1100f_row9_col4\" class=\"data row9 col4\" >AGO</td>\n",
       "                        <td id=\"T_1100f_row9_col5\" class=\"data row9 col5\" >5.38%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7fc44133d090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rpt_stats(df, asof, ['fatality', 'fr_spot'], show_nice_names=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Timeline Charts\n",
    "\n",
    "Cumulatives cases and deaths against the timeline for each country. Day 1 on the timeline is the first day when total cases exceeds 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monitor2 = ['CHN', 'BRA', 'RUS', 'IND', 'USA', 'ITA', 'GBR', 'SWE']\n",
    "\n",
    "timeline_chart(df, 'Cumulative cases on a common timeline',\n",
    "               cid=monitor2, y='cum_cases', log_scale='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "timeline_chart(df, 'Cumulative deaths on a common timeline',\n",
    "               cid=monitor2, y='cum_deaths', log_scale='', marker='')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Quick chart\n",
    "\n",
    "Generic chart to quickly plot different variables\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "chart(df, 'Fatality Rate', cid=monitor2, x='cum_cases', y='cum_deaths',\n",
    "      log_scale='', filter_timeline=True, marker='')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Inflection point - Where does the plateau start?\n",
    "\n",
    "Monitor the  daily cases / deaths against the China timeline. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monitor3 = ['ITA', 'FRA', 'W_EU','SWE', 'GBR', 'IND']\n",
    "chart(df, 'MA Cases v. Timeline', cid=monitor3, x='timeline', y='cum_deaths',\n",
    "      log_scale='', filter_timeline=True, marker='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "chart(df, 'PM Deaths v. Timeline', cid=monitor3 , x='timeline', y='pm_deaths',\n",
    "      log_scale='', filter_timeline=True, marker='')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}