How to Manipulate Strings in Pandas?
Last Updated :
05 Sep, 2020
Pandas Library provides multiple methods that can be used to manipulate string according to the required output. But first, let’s create a Pandas dataframe.
Python3
import pandas as pd
data = [[ 1 , "ABC KUMAR" , "xYZ" ], [ 2 , "BCD" , "XXY" ],
[ 3 , "CDE KUMAR" , "ZXX" ], [ 3 , "DEF" , "xYZZ" ]]
cfile = pd.DataFrame(data, columns = [ "SN" , "FirstName" , "LastName" ])
cfile
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Output:
“Pandas” library provides a “.str()” method that can be used to create any data of the data frame into a string, After that any string operation defined in python documentation or in this article can be used on that data.
Below is the code that illustrates some examples
Python3
result = cfile.FirstName. str .startswith( 'D' )
print (result)
result = cfile.LastName. str .contains( 'XX' )
print (result)
result = cfile.FirstName. str .split()
print (result)
result = cfile.LastName. str . len ()
print (result)
result = cfile.LastName. str .capitalize()
print (result)
result = cfile.LastName. str .upper()
print (result)
result = cfile.LastName. str .lower()
print (result)
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Output:
0 False
1 False
2 False
3 True
Name: FirstName, dtype: bool
0 False
1 True
2 True
3 False
Name: LastName, dtype: bool
0 [ABC, KUMAR]
1 [BCD]
2 [CDE, KUMAR]
3 [DEF]
Name: FirstName, dtype: object
0 3
1 3
2 3
3 4
Name: LastName, dtype: int64
0 Xyz
1 Xxy
2 Zxx
3 Xyzz
Name: LastName, dtype: object
0 XYZ
1 XXY
2 ZXX
3 XYZZ
Name: LastName, dtype: object
0 xyz
1 xxy
2 zxx
3 xyzz
Name: LastName, dtype: object
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