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')dropping nan in pandas dataframe
df.dropna(subset=['name', 'born'])pandas drop rows with nan in a particular column
In [30]: df.dropna(subset=[1]) #Drop only if NaN in specific column (as asked in the question)
Out[30]:
0 1 2
1 2.677677 -1.466923 -0.750366
2 NaN 0.798002 -0.906038
3 0.672201 0.964789 NaN
5 -1.250970 0.030561 -2.678622
6 NaN 1.036043 NaN
7 0.049896 -0.308003 0.823295
9 -0.310130 0.078891 NaNremove a rows in which three column has nan
df.dropna(subset=['col1', 'col2', 'col3', 'col4', 'col5', 'col6'], how='all', inplace=True)Copyright © 2021 Codeinu
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