drop if nan in column pandas
df = df[df['EPS'].notna()]dropping nan in pandas dataframe
df.dropna(subset=['name', 'born'])Returns a new DataFrame omitting rows with null values
# Returns a new DataFrame omitting rows with null values
df4.na.drop().show()
# +---+------+-----+
# |age|height| name|
# +---+------+-----+
# | 10| 80|Alice|
# +---+------+-----+when converting from dataframe to list delete nan values
a = [[y for y in x if pd.notna(y)] for x in df.values.tolist()]
print (a)
[['str', 'aad', 'asd'], ['ddd'], ['xyz', 'abc'], ['btc', 'trz', 'abd']]Copyright © 2021 Codeinu
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