drop if nan in column pandas
df = df[df['EPS'].notna()]
remove nan from list python
cleanedList = [x for x in countries if str(x) != 'nan']
remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')
dropping nan in pandas dataframe
df.dropna(subset=['name', 'born'])
python remove nan rows
df = df[df['my_var'].notna()]
drop columns with nan pandas
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwoman
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