In [1]:

    

import numpy as np
import pandas as pd
from pandas import Series,DataFrame


    

In [2]:

    

ser1 = Series([1,2,3,4,1,2,3,4])

ser1


    

    
Out[2]:





0    1
1    2
2    3
3    4
4    1
5    2
6    3
7    4
dtype: int64

In [3]:

    

ser1.replace(1,np.nan)


    

    
Out[3]:





0    NaN
1    2.0
2    3.0
3    4.0
4    NaN
5    2.0
6    3.0
7    4.0
dtype: float64

In [4]:

    

ser1.replace([1,4],[100,400])


    

    
Out[4]:





0    100
1      2
2      3
3    400
4    100
5      2
6      3
7    400
dtype: int64

In [5]:

    

ser1.replace([2,3],10)


    

    
Out[5]:





0     1
1    10
2    10
3     4
4     1
5    10
6    10
7     4
dtype: int64

In [7]:

    

ser1.replace({4:np.nan})


    

    
Out[7]:





0    1.0
1    2.0
2    3.0
3    NaN
4    1.0
5    2.0
6    3.0
7    NaN
dtype: float64

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