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@theSage21
Last active April 7, 2020 06:39
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"import pandas as pd\n",
"import requests\n",
"from bs4 import BeautifulSoup\n",
"import seaborn as sns\n",
"%pylab inline\n",
"from sklearn.linear_model import LinearRegression\n",
"import arrow\n",
"plt.style.use('ggplot')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Covid-19\n",
"\n",
"We use the database being maintained for https://www.covid19india.org/ , the link for which can be found at the bottom of the page.\n",
"\n",
"What we're trying to do here is to figure out how much this will spread.\n",
"\n",
"We assume that the disease spreads in an exponential fasion."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"r = requests.get('https://docs.google.com/spreadsheets/d/e/2PACX-1vSc_2y5N0I67wDU38DjDh35IZSIS30rQf7_NYZhtYYGU1jJYT6_kDx4YpF-qw0LSlGsBYP8pqM_a1Pd/pubhtml?format=csv')\n",
"\n",
"soup = BeautifulSoup(r.text, 'lxml')\n",
"\n",
"dfs = [pd.read_html(str(table), header=0)[0] for table in soup.findAll('table')]\n",
"\n",
"dfs[0]\n",
"\n",
"df = dfs[0]\n",
"df.columns = df.iloc[0].values\n",
"\n",
"df = df[2:].copy()\n",
"df\n",
"\n",
"df.columns = ['useless'] + list(df.columns[1:])\n",
"\n",
"df = df.drop(['useless', 'Patient Number', 'Status Change Date'], axis=1).dropna(how='all').copy()\n",
"\n",
"#df = df.drop('Patient Number', axis=1).dropna(how='all').copy()\n",
"\n",
"\n",
"df['date'] = df['Date Announced'].apply(lambda x: arrow.get(x, 'DD/MM/YYYY') if isinstance(x, str) else None)\n",
"df = df.dropna(how='all').copy()\n",
"df['infected'] = df['Current Status'] == 'Hospitalized'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4637 2020-04-07\n"
]
}
],
"source": [
"df['today'] = df['date'].apply(lambda x: x.date() == arrow.utcnow().date())\n",
"df = df.loc[~df['today']]\n",
"cases = df[['infected', 'date']].copy()\n",
"counts = cases.groupby('date')['infected'].count()\n",
"\n",
"total_cases, today = df['infected'].sum(), arrow.utcnow().date()\n",
"\n",
"print(total_cases, today)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## How closely is this following an exponentiation curve?"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"daily_cases = counts.sort_index().values\n",
"days = np.arange(len(daily_cases))\n",
"\n",
"logged = np.log(daily_cases)\n",
"\n",
"lr = LinearRegression()\n",
"lr.fit(days.reshape(-1, 1), logged)\n",
"def expectation(x, logged=True):\n",
" x = x.copy()\n",
" x = x * lr.coef_.flatten() + lr.intercept_\n",
" x = np.exp(x) if logged else x\n",
" return x"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0,0.5,'New cases')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.plot(daily_cases, marker='.')\n",
"plt.title(f'Daily new cases reported so far: { str(today)}')\n",
"plt.xlabel('Days')\n",
"plt.ylabel('New cases')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It looks exponential. The only way to find out is to do some regression and find the coefficients.\n",
"\n",
"## What's the trend that India is following"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x7f4c50d6f048>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"expected_cases = expectation(days)\n",
"\n",
"plt.plot(days, daily_cases, label='Actual')\n",
"plt.plot(days, expected_cases, label='Expected')\n",
"plt.legend()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Expecting cases today: 520 892 1530\n"
]
}
],
"source": [
"std = np.sqrt(np.sum(np.power(logged - expectation(days, logged=False), 2)) / days.shape[0])\n",
"std\n",
"\n",
"p = expectation(days[-1] + 1, logged=False)\n",
"low, high = p - std, p + std\n",
"low, high = np.exp(low), np.exp(high)\n",
"low, high = int(low[0]), int(high[0])\n",
"pred = int(np.exp(p)[0])\n",
"print('Expecting cases today: ',low, pred, high)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## What can we expect in one week?"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def in_future(n_days_in_future = 7):\n",
"\n",
" days_future = np.concatenate([days, days[-1] + np.arange(1, n_days_in_future)])\n",
"\n",
" p = expectation(days_future, logged=False)\n",
" low, predicted, high = np.exp(p-std), np.exp(p), np.exp(p+std)\n",
" max_predicted = int(np.ceil(np.max(high)))\n",
"\n",
" plt.figure(figsize=(15, 10))\n",
"\n",
" plt.plot([days[-1]+1]*10, np.linspace(0,max_predicted, 10), marker='o', label=f'Today : { str(today) }')\n",
" plt.plot(low, marker='.',label=f'+{n_days_in_future} best')\n",
" plt.plot(high, marker='.', label=f'+{n_days_in_future} worst')\n",
" plt.plot(predicted, marker='.', label=f'+{n_days_in_future} days')\n",
" plt.plot(daily_cases, marker='.', label='Actual cases')\n",
" plt.xlabel('Days')\n",
" plt.ylabel('New cases')\n",
"\n",
" low, high = np.sum(low[-n_days_in_future:]), np.sum(high[-n_days_in_future:])\n",
" low, high = map(int, (low, high))\n",
" predicted = int(np.sum(predicted[-n_days_in_future:]))\n",
" title = f'{low} to {high} new cases expected in +{n_days_in_future} days.\\n'\n",
" title += f'{today} : {total_cases} infected till date.'\n",
" plt.title(title)\n",
" plt.legend()\n",
"\n",
"WEEK = 7\n",
"in_future(1*WEEK)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"That last part shows that we're not following an exponential at now. Perhaps in the coming days we should change the equation and make new projections."
]
}
],
"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": "3.6.9"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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