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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)

Output:

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