Select Columns with Specific Data Types in Pandas Dataframe

Last Updated : 02 Dec, 2020

In this article, we will see how to select columns with specific data types from a dataframe. This operation can be performed using the DataFrame.select_dtypes() method in pandas module.

Syntax: DataFrame.select_dtypes(include=None, exclude=None)
Parameters :
include, exclude : A selection of dtypes or strings to be included/excluded. At least one of these parameters must be supplied.
Return : The subset of the frame including the dtypes in include and excluding the dtypes in exclude.

Step-by-step Approach:

First, import modules then load the dataset.

Python3

# import required module 
import pandas as pd 
  
# assign dataset 
df = pd.read_csv("train.csv") 

Then we will find types of data present in our dataset using dataframe.info() method.

Python3

# display description 
# of the dataset 
df.info() 

Output:

Now, we will use DataFrame.select_dtypes() to select a specific datatype.

Python3

# store columns with specific data type 
integer_columns = df.select_dtypes(include=['int64']).columns 
float_columns = df.select_dtypes(include=['float64']).columns 
object_columns = df.select_dtypes(include=['object']).columns 

Finally, display the column having a particular data type.

Python3

# display columns 
print('\nint64 columns:\n', integer_columns) 
print('\nfloat64 columns:\n', float_columns) 
print('\nobject columns:\n', object_columns) 

Output:

Below is the complete program based on the above approach:

Python3

# import required module 
import pandas as pd 
  
# assign dataset 
df = pd.read_csv("train.csv") 
  
# store columns with specific data type 
integer_columns = df.select_dtypes(include=['int64']).columns 
float_columns = df.select_dtypes(include=['float64']).columns 
object_columns = df.select_dtypes(include=['object']).columns 
  
# display columns 
print('\nint64 columns:\n',integer_columns) 
print('\nfloat64 columns:\n',float_columns) 
print('\nobject columns:\n',object_columns) 

Output:

Example:

Here we are going to extract columns of the below dataset:

Python3

# import required module 
import pandas as pd 
from vega_datasets import data 
  
# assign dataset 
df = data.seattle_weather() 
  
# display dataset 
df.sample(10) 

Output:

Now, we are going to display all the columns having float64 as the data type.

Python3

# import required module 
import pandas as pd 
from vega_datasets import data 
  
# assign dataset 
df = data.seattle_weather() 
  
# display description 
# of dataset 
df.info() 
  
# store columns with specific data type 
columns = df.select_dtypes(include=['float64']).columns 
  
# display columns 
print('\nColumns:\n', columns) 