drop if nan in column pandas
df = df[df['EPS'].notna()]pandas drop row with nan
import pandas as pd
df = pd.DataFrame({'values_1': ['700','ABC','500','XYZ','1200'],
'values_2': ['DDD','150','350','400','5000']
})
df = df.apply (pd.to_numeric, errors='coerce')
df = df.dropna()
df = df.reset_index(drop=True)
print (df)drop column with nan values
fish_frame = fish_frame.dropna(axis = 1, how = 'all')dropna threshold
#dropping columns having more than 50% missing values(1994/2==1000)
df=df.dropna(thresh=1000,axis=1)Copyright © 2021 Codeinu
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