How to Create Dummy Variables in Python with Pandas?

A dataset may contain various type of values, sometimes it consists of categorical values. So, in-order to use those categorical value for programming efficiently we create dummy variables. A dummy variable is a binary variable that indicates whether a separate categorical variable takes on a specific value. 

Explanation:

As you can see three dummy variables are created for the three categorical values of the temperature attribute. We can create dummy variables in python using get_dummies() method.

Syntax: pandas.get_dummies(data, prefix=None, prefix_sep=’_’,)

Parameters:

• data= input data i.e. it includes pandas data frame. list . set . numpy arrays etc.
• prefix= Initial value
• prefix_sep= Data values separation.

Return Type: Dummy variables.

Step-by-step Approach:

• Import necessary modules
• Consider the data
• Perform operations on data to get dummies

Example 1: 

Python3

# import required modules
import pandas as pd
import numpy as np

# create dataset
df = pd.DataFrame({'Temperature': ['Hot', 'Cold', 'Warm', 'Cold'],
                   })

# display dataset
print(df)

# create dummy variables
pd.get_dummies(df)

Output:

Example 2:

Consider List arrays to get dummies

Python3

# import required modules
import pandas as pd
import numpy as np

# create dataset
s = pd.Series(list('abca'))

# display dataset
print(s)

# create dummy variables
pd.get_dummies(s)

Output:

Example 3:

Here is another example, to get dummy variables.

Python3

# import required modules
import pandas as pd
import numpy as np

# create dataset
df = pd.DataFrame({'A': ['hello', 'vignan', 'geeks'],
                   'B': ['vignan', 'hello', 'hello'],
                   'C': [1, 2, 3]})

# display dataset
print(df)

# create dummy variables
pd.get_dummies(df)

Output: