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Combine two columns of text in Pandas DataFrame

Given a DataFrame, we have to combine the text of two columns.
Submitted by Pranit Sharma, on April 13, 2022

Columns are the different fields that contains their particular values when we create a DataFrame. We can perform certain operations on both rows & column values. Sometimes, we might need to combine the text of two columns. Pandas allows us to achieve this task using the cat() function.

pandas.Series.str.cat() Method

The cat is the short form for concatenation. The cat() method is used for concatenating two or more strings. It takes the value of a particular column as an input along with the value of another column which has to be combined.

Syntax:

df['new_col_name'] = df['col_1_name'].str.cat(df['col_2_name']) 

Parameters: It takes a parameter sep, where sep means separator, it is the special character that comes between the combined strings.

To work with Python Pandas, we need to import the pandas library. Below is the syntax,

import pandas as pd

Let us understand with the help of an example.

Example:

# Importing pandas package
import pandas as pd

# Creating a dictionary of student marks
d = {
    "Name":['Hari','Mohan','Neeti','Shaily'],
    "Age":[25,36,26,21],
    "Gender":['Male','Male','Female','Female'],
    "Profession":['Doctor','Teacher','Singer','Student'],
    "Title":['Mr','Mr','Ms','Ms']
}

# Now, Create DataFrame
df = pd.DataFrame(d)

# Printing the original DataFrame
print("Original DataFrame:\n")
print(df,"\n\n")

# Now, Combine the values of Name and 
# title using str.cat() function
df['Full_Name'] = df['Title'].str.cat(df['Name'], sep =".")

# Now, Printing the modified DataFrame
print("Combined column:\n")
print(df)

Output:

Original DataFrame:

     Name  Age  Gender Profession Title
0    Hari   25    Male     Doctor    Mr
1   Mohan   36    Male    Teacher    Mr
2   Neeti   26  Female     Singer    Ms
3  Shaily   21  Female    Student    Ms 


Combined column:

     Name  Age  Gender Profession Title  Full_Name
0    Hari   25    Male     Doctor    Mr    Mr.Hari
1   Mohan   36    Male    Teacher    Mr   Mr.Mohan
2   Neeti   26  Female     Singer    Ms   Ms.Neeti
3  Shaily   21  Female    Student    Ms  Ms.Shaily

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