Add a column with default values in pandas dataframe python

In This Section we will be focusing on how to add a column with default values in pandas dataframe, There are multiple ways to do it, like adding a column with default value at the first position and last position (start and end of the dataframe) , adding multiple columns with default values to the dataframe in pandas. let’s look at each of these cases in pandas with an example for each.

  • Assign or replace existing column with empty or null values in pandas python
  • Add a column with default values in pandas dataframe.
  • Add a column with default values at first position of the dataframe in pandas (start of the dataframe)
  • Add multiple columns with default values in pandas (to end of the dataframe)
  • Add multiple columns with default values to the start of the dataframe in pandas

 

Create Dataframe:

 

## create dataframe

import pandas as pd
import numpy as np
#Create a DataFrame
import pandas as pd
import numpy as np
d = { 'Name':['Alisa','Bobby','Cathrine','Jodha','Raghu','Ram'],
'Age':[26,23,23,23,23,24],
'Score':[85,31,55,55,31,77],
'City':['Newyork','Seattle','Toronto','California','Delhi','Mumbai']}

df = pd.DataFrame(d,columns=['Name','Age','Score','City'])
df

The Resultant dataframe is

Add-a-column-with-default-values-in-pandas-dataframe-python-1

 

 

Add new column with default values in pandas: Method 1

In the below example we have added the new column with default value in pandas

 

#### add new column with default values in pandas: Method 1
df["University"] = 'MIT'
df

As the result University column is added to the pandas dataframe with default value –“MIT” as shown below

Add-a-column-with-default-values-in-pandas-dataframe-python-2

 

 

 

Add new column with default values in pandas: Method 2

In the below example we have added the new column with default value in pandas, we have used lambda function to assign the default value throughout the column

 
#### add new column with default values in pandas: Method 2

df["University"] = df.apply(lambda _: 'MIT', axis=1)

df

As the result University column is added to the pandas dataframe with default value –“MIT” as shown below

Add-a-column-with-default-values-in-pandas-dataframe-python-3 (1)

 

 

Add new column with default values in pandas: Method 3

In the below example we have added the new column with default value in pandas, we have used assign function to assign the default value throughout the column

 

 
#### add new column with default values in pandas: Method 3

df2 = df.assign(University="MIT")
df2

As the result University column is added to the pandas dataframe with default value –“MIT” as shown below

Add-a-column-with-default-values-in-pandas-dataframe-python-3

 

 

 

Add new column with default values to start of the dataframe in pandas

In the below example we have added the new column with default values to the start of the dataframe .i.e. to the first position of dataframe in pandas, we have used insert function to assign the default value to the first position

 

#### add new column to 1st position of the dataframe in pandas: Method 1
df.insert(0,"University", "MIT")
df

As the result University column is added to 1st position of the pandas dataframe with default value –“MIT” as shown below

Add-a-column-with-default-values-in-pandas-dataframe-python-4

 

 

Add multiple columns with default values in pandas dataframe

In the below example we have added the multiple columns with default values to the dataframe . we have used assign function to assign the default values multiple columns at once.

 

#### add multiple columns with default values in pandas : Method 1
df2 = df.assign(University="MIT", University_code = 3014)
df2

As the result University column and University_code column is created in the default value is created at once as shown below

Add-a-column-with-default-values-in-pandas-dataframe-python-5

 

 

 

pandas Add multiple columns with default values to start of the dataframe

In the below example we have added the multiple columns with default values to the start of the dataframe.  .i.e. to the first position of dataframe in pandas, we have used insert function to assign the default value to the first position

 
#### add multiple columns with default values in pandas at start of the dataframe
df.insert(0,"University", "MIT")
df.insert(1,"University_code", 3014)
df

As the result University column and University_code column is created to the start of the dataframe, with the default value is created at once as shown below

Add-a-column-with-default-values-in-pandas-dataframe-python-6

 

 

 

Author

  • Sridhar Venkatachalam

    With close to 10 years on Experience in data science and machine learning Have extensively worked on programming languages like R, Python (Pandas), SAS, Pyspark.

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