How to merge (concatenate) two or more dataframe columns into one column with pandas ?

Examples of how to merge (concatenate) two columns into one with pandas:

Merge two or more dataframe columns of strings with pandas

Let's first create a dataframe with pandas

import pandas as pd
import numpy as np

data = {'First_Name':['April','Emory','David','Alice','Virginia'],
        'Last_Name':['Reiter','Miller','Ballin','Trotter','Rios'],
        'Middle_Name':['G.','','H.G','',''],
        'Age':[42,24,12,32,56]}

df = pd.DataFrame(data=data)

print(df)

gives

  First_Name Last_Name Middle_Name  Age
0      April    Reiter          G.   42
1      Emory    Miller               24
2      David    Ballin         H.G   12
3      Alice   Trotter               32
4   Virginia      Rios               56

Merge two columns of strings

To merge two columns of strings, a straightforward solution is to do:

df['First_Name'] + df['Last_Name']

gives then

0     AprilReiter
1     EmoryMiller
2     DavidBallin
3    AliceTrotter
4    VirginiaRios
dtype: object

To add a space:

df['First_Name'] + ' ' + df['Last_Name']

gives

0     April Reiter
1     Emory Miller
2     David Ballin
3    Alice Trotter
4    Virginia Rios
dtype: object

Another solution is to use pandas.DataFrame.agg:

df[['First_Name','Last_Name']].agg(' '.join, axis=1)

gives

0     April Reiter
1     Emory Miller
2     David Ballin
3    Alice Trotter
4    Virginia Rios
dtype: object

Another example, aggregating three columns

df[['First_Name','Middle_Name','Last_Name']].agg(' '.join, axis=1)

gives

0     April G. Reiter
1       Emory  Miller
2    David H.G Ballin
3      Alice  Trotter
4      Virginia  Rios
dtype: object

Create a new Full_Name column:

df['Full_Name'] = df[['First_Name','Middle_Name','Last_Name']].agg(' '.join, axis=1)

print(df)

gives

  First_Name Last_Name Middle_Name  Age         Full_Name
0      April    Reiter          G.   42   April G. Reiter
1      Emory    Miller               24     Emory  Miller
2      David    Ballin         H.G   12  David H.G Ballin
3      Alice   Trotter               32    Alice  Trotter
4   Virginia      Rios               56    Virginia  Rios

Note that some rows of the Full_Name column has two spaces. To fix that:

df['Full_Name'].str.replace("  "," ")

gives

0     April G. Reiter
1        Emory Miller
2    David H.G Ballin
3       Alice Trotter
4       Virginia Rios
Name: Full_Name, dtype: object

Merge a column of strings with a column of integers

To merge a column of strings with a column of integers it is necessary to first convert the numbers into a string. To do that a solution is to use astype():

df['Last_Name'] + ' ' + df['Age'].astype(str)

gives

0     Reiter 42
1     Miller 24
2     Ballin 12
3    Trotter 32
4       Rios 56
dtype: object

Another example using agg():

df[['Last_Name','Age']].apply(lambda x : x.astype(str)).agg(' '.join, axis=1)

gives

0     Reiter 42
1     Miller 24
2     Ballin 12
3    Trotter 32
4       Rios 56
dtype: object

Merge columns of numbers

Let's create a new dataframe

import pandas as pd
import numpy as np

data = {'First_Name':['April','Emory','David','Alice','Virginia'],
        'Last_Name':['Reiter','Miller','Ballin','Trotter','Rios'],
        'Middle_Name':['G.','','H.G','',''],
        'Age':[42,24,12,32,56],
        'Score':[2,10,5,3,10]}

df = pd.DataFrame(data=data)

print(df)

gives

  First_Name Last_Name Middle_Name  Age  Score
0      April    Reiter          G.   42      2
1      Emory    Miller               24     10
2      David    Ballin         H.G   12      5
3      Alice   Trotter               32      3
4   Virginia      Rios               56     10

Then if you do

print( df['Age'] + df['Score'] )

you will basically add the two columns together:

0    44
1    34
2    17
3    35
4    66
dtype: int64

To concatenate the two numbers:

print( df['Age'].astype(str) + ' -- '+ df['Score'].astype(str) )

gives

0     42 -- 2
1    24 -- 10
2     12 -- 5
3     32 -- 3
4    56 -- 10
dtype: object