text_plain_output_1.png
import pandas as pd

import pandas as pd
pd.set_option('display.max_columns', 1000)
pd.set_option('display.max_rows', 1000)

train = pd.read_csv('../input/covid19-global-forecasting-week-4/train.csv', parse_dates=['Date'])
test = pd.read_csv('../input/covid19-global-forecasting-week-4/test.csv', parse_dates=['Date'])
countryinfo = pd.read_csv('../input/countryinfo/covid19countryinfo.csv', parse_dates=['quarantine', 'schools', 'publicplace', 'nonessential', 'gathering'])
states = pd.read_csv('../input/covid19-in-usa/us_states_covid19_daily.csv')
state_pops = pd.read_csv('../input/us-state-populations-2018/State Populations.csv')

dataset = train[train['Date'] == '2020-04-12'].sort_values(by=['ConfirmedCases'], ascending=False).head(100)

merged = dataset.merge(countryinfo, left_on=['Country_Region', 'Province_State'], right_on=['country', 'region'], how='left').merge(state_pops, left_on=['Province_State'], right_on=['State'], how='left')[['Id', 'Country_Region', 'Province_State', 'Date', 'ConfirmedCases', 'Fatalities', 'pop', 'density', 'quarantine', 'schools', 'publicplace', 'nonessential', 'gathering', '2018 Population']]
merged.head(20)
merged.dtypes