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)remove rows or columns with NaN value
df.dropna() #drop all rows that have any NaN values
df.dropna(how='all')drop columns with nan pandas
>>> df.dropna(axis='columns')
name
0 Alfred
1 Batman
2 Catwomanwhen 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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