text_html_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import warnings

import matplotlib.pyplot as plt
plt.style.use('dark_background')
import warnings
warnings.filterwarnings('ignore')
import seaborn

train_data = pd.read_csv('/kaggle/input/covid19-global-forecasting-week-4/train.csv')
test_data = pd.read_csv('/kaggle/input/covid19-global-forecasting-week-4/test.csv')

train_data.rename(columns={'Country_Region': 'Country'}, inplace=True)
test_data.rename(columns={'Country_Region': 'Country'}, inplace=True)
train_data.rename(columns={'Province_State': 'Province'}, inplace=True)
test_data.rename(columns={'Province_State': 'Province'}, inplace=True)

india = train_data.loc[train_data['Country'] == 'India']
plt.xticks(rotation=90)

confirmed = train_data.groupby('Date').sum()['ConfirmedCases'].reset_index()
deaths = train_data.groupby('Date').sum()['Fatalities'].reset_index()
plt.figure(figsize=(22, 9))
plt.bar(confirmed['Date'], confirmed['ConfirmedCases'])
plt.title('World Circumstances')
plt.bar(deaths['Date'], deaths['Fatalities'])
plt.xticks(rotation=90)
plt.show()