How to filter a Pandas Series in Python

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Series is a data structure type that stores one dimensional labeled data in Pandas module in Python. When a Series is created, its value can be filtered using loc() function, and the result can be stored into a new Series. Filtering conditional can be any of combination of conditional statements. isin() function can also be used to match specific values in filtering statement. Next code examples show implementation of these operations in Python IDE.

#Import Pandas and Numpy module
import pandas as pd
import numpy as np
#Create an array of 5 elements
T = np.array([32, 301, 19, 7, 13])
U = pd.Series(T)
U
#output
0     32
1    301
2     19
3      7
4     13
dtype: int32
#filtering value larger than 10 from Series and save to a new Series
R1 = U.loc[lambda x: x > 10]
R1
#output
0     32
1    301
2     19
4     13
dtype: int32
#Filtering values larger than 10 and smaller than 25
#result saved to a new Series
R2 = U.loc[lambda x: (x > 10) & (x < 25)]
R2
#output
2    19
4    13
dtype: int32
#Filtering values smaller than 10 or larger than 25
#and result saved to a new Series
R3=U.loc[lambda x: (x < 10) | (x > 25)]
R3
#output
0     32
1    301
3      7
dtype: int32
#Filtering values if they match any elements in a specified list
#result saved to a new Series
R4 = U[U.isin([32,301,13,100])]
R4
#output
0     32
1    301
4     13
dtype: int32

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