Pandas Insert Method

Pandas Insert Method

Suraj Joshi Mar-21, 2022 Jan-16, 2021 Pandas Pandas DataFrame Column
  1. pandas.DataFrame.insert() Method in Python
  2. Set allow_duplicates = True in the insert() Method to Add Already Existing Column

This tutorial explains how we can use the insert() method for a Pandas DataFrame to insert a column in the DataFrame.

import pandas as pd

countries_df = pd.DataFrame({
    'Country': ["Nepal","Switzerland","Germany","Canada"],
    'Continent': ["Asia","Europe","Europe","North America"],
    'Primary Language':["Nepali","French","German","English"]
})
print("Countries DataFrame:")
print(countries_df,"\n")

Output:

Countries DataFrame:
       Country      Continent Primary Language
0        Nepal           Asia           Nepali
1  Switzerland         Europe           French
2      Germany         Europe           German
3       Canada  North America          English

We will use the countries_df DataFrame shown in the above example to explain how we can use the insert() method for a Pandas DataFrame to insert a column in the DataFrame.

pandas.DataFrame.insert() Method in Python

Syntax

DataFrame.insert(loc,
                column,
                value,
                allow_duplicates=False)

It inserts the column named column into the DataFrame with values specified by value at location loc.

Insert a Column Having the Same Value for All Rows Using the insert() Method

import pandas as pd

countries_df = pd.DataFrame({
    'Country': ["Nepal","Switzerland","Germany","Canada"],
    'Continent': ["Asia","Europe","Europe","North America"],
    'Primary Language':["Nepali","French","German","English"]
})
print("Countries DataFrame:")
print(countries_df,"\n")

countries_df.insert(3,"Capital","Unknown")

print("Countries DataFrame after inserting Capital column:")
print(countries_df)

Output:

Countries DataFrame:
       Country      Continent Primary Language
0        Nepal           Asia           Nepali
1  Switzerland         Europe           French
2      Germany         Europe           German
3       Canada  North America          English

Countries DataFrame after inserting Capital column:
       Country      Continent Primary Language  Capital
0        Nepal           Asia           Nepali  Unknown
1  Switzerland         Europe           French  Unknown
2      Germany         Europe           German  Unknown
3       Canada  North America          English  Unknown

It inserts the column Capital in the countries_df DataFrame at position 3 with the same value of the column for all rows set to Unknown.

The position starts from 0 and hence position 3 refers to the 4th column in the DataFrame.

Insert a Column in a DataFrame Specifying Value for Each Row

If we want to specify the values of each row for the column to be inserted using the insert() method, we can pass a list of values as a value argument in the insert() method.

import pandas as pd

countries_df = pd.DataFrame({
    'Country': ["Nepal","Switzerland","Germany","Canada"],
    'Continent': ["Asia","Europe","Europe","North America"],
    'Primary Language':["Nepali","French","German","English"]
})
print("Countries DataFrame:")
print(countries_df,"\n")

capitals=["Kathmandu","Zurich","Berlin","Ottawa"]

countries_df.insert(2,"Capital",capitals)

print("Countries DataFrame after inserting Capital column:")
print(countries_df)

Output:

Countries DataFrame:
       Country      Continent Primary Language
0        Nepal           Asia           Nepali
1  Switzerland         Europe           French
2      Germany         Europe           German
3       Canada  North America          English

Countries DataFrame after inserting Capital column:
       Country      Continent    Capital Primary Language
0        Nepal           Asia  Kathmandu           Nepali
1  Switzerland         Europe     Zurich           French
2      Germany         Europe     Berlin           German
3       Canada  North America     Ottawa          English

It inserts the column Capital in the DataFrame countries_df at position 2 with specified values of each row for the Capital column in the DataFrame.

Set allow_duplicates = True in the insert() Method to Add Already Existing Column

import pandas as pd

countries_df = pd.DataFrame({
    'Country': ["Nepal","Switzerland","Germany","Canada"],
    'Continent': ["Asia","Europe","Europe","North America"],
    'Primary Language':["Nepali","French","German","English"],
    'Capital':["Kathmandu","Zurich","Berlin","Ottawa"]
})
print("Countries DataFrame:")
print(countries_df,"\n")

capitals=["Kathmandu","Zurich","Berlin","Ottawa"]

countries_df.insert(4,"Capital",capitals,allow_duplicates = True)

print("Countries DataFrame after inserting Capital column:")
print(countries_df)

Output:

Countries DataFrame:
       Country      Continent Primary Language    Capital
0        Nepal           Asia           Nepali  Kathmandu
1  Switzerland         Europe           French     Zurich
2      Germany         Europe           German     Berlin
3       Canada  North America          English     Ottawa

Countries DataFrame after inserting Capital column:
       Country      Continent Primary Language    Capital    Capital
0        Nepal           Asia           Nepali  Kathmandu  Kathmandu
1  Switzerland         Europe           French     Zurich     Zurich
2      Germany         Europe           German     Berlin     Berlin
3       Canada  North America          English     Ottawa     Ottawa

It adds the column Capital to the countries_df DataFrame even though the column Capital already exists in the countries_df DataFrame.

If we try to insert the column that already exists in the DataFrame without setting allow_duplicates = True in the insert() method, it will throw us an error with the message: ValueError: cannot insert column, already exists.

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