Open In App

How to Manipulate Strings in Pandas?

Last Updated : 05 Sep, 2020
Summarize
Comments
Improve
Suggest changes
Share
Like Article
Like
Report

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

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
# find firstname starting with 'D'
result = cfile.FirstName.str.startswith('D')
print(result)

# find lasttname containing 'XX'
result = cfile.LastName.str.contains('XX')
print(result)


# split FirstName on the basis of ' '
result = cfile.FirstName.str.split()
print(result)


# find length of lasttname
result = cfile.LastName.str.len()
print(result)

# Capitalize the first Letter of LastName
result = cfile.LastName.str.capitalize()
print(result)

# Capitalize all Letter of LastName
result = cfile.LastName.str.upper()
print(result)

# Convert all Letter of LastName to lowercase
result = cfile.LastName.str.lower()
print(result)

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

Next Article

Similar Reads