drop if nan in column pandas
df = df[df['EPS'].notna()]drop null rows pandas
df.dropna()dropna for specific column pandas
df = df[df['EPS'].notna()] #instead of dropping, take another DF with non-na valuesdropping nan in pandas dataframe
df.dropna(subset=['name', 'born'])dropna in specific column pandas
df.dropna(subset = ['column1', 'column2'], inplace = True)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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