drop if nan in column pandas
df = df[df['EPS'].notna()]remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')numpy remove rows containing nan
a = a[~(np.isnan(a).any(axis=1))] # removes rows containing at least one nan
a = a[~(np.isnan(a).all(axis=1))] # removes rows containing all nandropping 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|
# +---+------+-----+Copyright © 2021 Codeinu
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