Python - Select columns with specific datatypes

To select columns with specific datatypes, use the select_dtypes() method and the include parameter. At first, create a DataFrame with 2 columns −

dataFrame = pd.DataFrame(
   {
      "Student": ['Jack', 'Robin', 'Ted', 'Marc', 'Scarlett', 'Kat', 'John'],"Roll Number": [ 5, 10, 3, 8, 2, 9, 6]
   }
)

Now, select the 2 columns with their respective specific datatype −

column1 = dataFrame.select_dtypes(include=['object']).columns
column2 = dataFrame.select_dtypes(include=['int64']).columns

Example

Following is the code −

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
   {
      "Student": ['Jack', 'Robin', 'Ted', 'Marc', 'Scarlett', 'Kat', 'John'],"Roll Number": [ 5, 10, 3, 8, 2, 9, 6]
   }
)

print"DataFrame ...\n",dataFrame

print"\nInfo of the entire dataframe:\n"

# get the description
print(dataFrame.info())

# select columns with specific datatype
column1 = dataFrame.select_dtypes(include=['object']).columns
column2 = dataFrame.select_dtypes(include=['int64']).columns

print"Column 1 with object type = ",column1
print"Column 2 with int64 type = ",column2

Output

This will produce the following output −

DataFrame ...
   Roll Number   Student
0            5      Jack
1           10     Robin
2            3       Ted
3            8      Marc
4            2  Scarlett
5            9       Kat
6            6      John

Info of the entire dataframe:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 7 entries, 0 to 6
Data columns (total 2 columns):
Roll Number    7  non-null int64
Student        7  non-null object
dtypes: int64(1), object(1)
memory usage: 184.0+ bytes
None
Column 1 with object type = Index([u'Student'], dtype='object')
Column 2 with int64 type = Index([u'Roll Number'], dtype='object')