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Initial EDA of Brasil.io data of COVID 19
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{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Description</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>date</th>\n",
" <td>date</td>\n",
" </tr>\n",
" <tr>\n",
" <th>state</th>\n",
" <td>state</td>\n",
" </tr>\n",
" <tr>\n",
" <th>city</th>\n",
" <td>city</td>\n",
" </tr>\n",
" <tr>\n",
" <th>place_type</th>\n",
" <td>place_type</td>\n",
" </tr>\n",
" <tr>\n",
" <th>confirmed</th>\n",
" <td>Number of Confirmed Cases</td>\n",
" </tr>\n",
" <tr>\n",
" <th>deaths</th>\n",
" <td>deaths</td>\n",
" </tr>\n",
" <tr>\n",
" <th>is_last</th>\n",
" <td>Latest Update</td>\n",
" </tr>\n",
" <tr>\n",
" <th>estimated_population_2019</th>\n",
" <td>estimated_population_2019</td>\n",
" </tr>\n",
" <tr>\n",
" <th>city_ibge_code</th>\n",
" <td>city_ibge_code</td>\n",
" </tr>\n",
" <tr>\n",
" <th>confirmed_per_100k_inhabitants</th>\n",
" <td>Number of Confirmed Cases per 100k Inhabitants</td>\n",
" </tr>\n",
" <tr>\n",
" <th>death_rate</th>\n",
" <td>death_rate</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Description\n",
"date date\n",
"state state\n",
"city city\n",
"place_type place_type\n",
"confirmed Number of Confirmed Cases\n",
"deaths deaths\n",
"is_last Latest Update\n",
"estimated_population_2019 estimated_population_2019\n",
"city_ibge_code city_ibge_code\n",
"confirmed_per_100k_inhabitants Number of Confirmed Cases per 100k Inhabitants\n",
"death_rate death_rate"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.DataFrame(list(data_dict.values()), columns=[\"Description\"], index=list(data_dict.keys()))"
]
},
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