我的输入数据是这样的
SL.NO Name
1 KING BATA
2
3
4 AGS
5 FORMULA GROWTH
6
7 Bag
Output
SL.NO Name Value
1 KING BATA Present
2 Not Present
3 Not Present
4 AGS Present
5 FORMULA GROWTH Present
6 Not Present
7 Bag Present
如何处理 pandas 中的 null、空白和垃圾值？
Use numpy.where https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html:
#If missing value is NaN
df['Value'] = np.where(df['Name'].isnull(), 'Present', 'Not Present')
Or:
#If missing value is empty string
df['Value'] = np.where(df['Name'].eq(''), 'Present', 'Not Present')
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