text_html_output_1.png
import pandas as pd

import os, gc, pickle, copy, datetime, warnings
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import lightgbm as lgb
from sklearn import metrics
pd.set_option('display.max_columns', 100)
warnings.filterwarnings('ignore')

df_train = pd.read_csv('../input/covid19-global-forecasting-week-4/train.csv')
print(df_train.shape)
df_train.tail()