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14 changes: 7 additions & 7 deletions 2-Working-With-Data/07-python/notebook-covidspread.ipynb
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}
],
"source": [
"infected.loc['US'][2:].plot()\n",
"recovered.loc['US'][2:].plot()\n",
"infected.loc['US'][3:].plot()\n",
"recovered.loc['US'][3:].plot()\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"> **Note** how we use `[2:]` to remove first two elements of a sequence that contain geolocation of a country. We can also drop those two columns altogether:"
"> **Note** how we use `[3:]` to remove first two elements of a sequence that contain geolocation of a country. We can also drop those two columns altogether:"
]
},
{
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"metadata": {},
"outputs": [],
"source": [
"infected.drop(columns=['Lat','Long'],inplace=True)\n",
"recovered.drop(columns=['Lat','Long'],inplace=True)\n",
"deaths.drop(columns=['Lat','Long'],inplace=True)"
"infected.drop(columns=['Lat','Long','Province/State'],inplace=True)\n",
"recovered.drop(columns=['Lat','Long','Province/State'],inplace=True)\n",
"deaths.drop(columns=['Lat','Long','Province/State'],inplace=True)"
]
},
{
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],
"source": [
"def mkframe(country):\n",
" df = pd.DataFrame({ 'infected' : infected.loc[country] ,\n",
" df = pd.DataFrame({ 'infected' : infected.loc[country],\n",
" 'recovered' : recovered.loc[country],\n",
" 'deaths' : deaths.loc[country]})\n",
" df.index = pd.to_datetime(df.index)\n",
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1,499 changes: 0 additions & 1,499 deletions 2-Working-With-Data/07-python/notebook.ipynb

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