Get the datatypes of columns of a Pandas DataFrame

Last Updated : 10 Aug, 2021

Let us see how to get the datatypes of columns in a Pandas DataFrame. TO get the datatypes, we will be using the dtype() and the type() function.
Example 1 :

python

# importing the module
import pandas as pd
  
# creating a DataFrame    
dictionary = {'Names':['Simon', 'Josh', 'Amen', 'Habby', 
                       'Jonathan', 'Nick', 'Jake'], 
              'Countries':['AUSTRIA', 'BELGIUM', 'BRAZIL', 
                           'JAPAN', 'FRANCE', 'INDIA', 'GERMANY'],
              'Boolean':[True, False, False, True, 
                         True, False, True],
              'HouseNo':[231, 453, 723, 924, 784, 561, 403],
              'Location':[12.34, 45.67, 03.45, 17.23, 
                          83.12, 90.45, 84.34]}
table = pd.DataFrame(dictionary, columns = ['Names', 'Countries', 
                                            'Boolean', 'HouseNo', 'Location'])
  
print("Data Types of The Columns in Data Frame")
display(table.dtypes)
  
print("Data types on accessing a single column of the Data Frame ")
print("Type of Names Column : ", type(table.iloc[:, 0]))
print("Type of HouseNo Column : ", type(table.iloc[:, 3]), "\n")
  
print("Data types of individual elements of a particular columns Data Frame ")
print("Type of Names Column Element : ", type(table.iloc[:, 0][1]))
print("Type of Boolean Column Element : ", type(table.iloc[:, 2][2]))
print("Type of HouseNo Column Element : ", type(table.iloc[:, 3][4]))
print("Type of Location Column Element : ", type(table.iloc[:, 4][0]))

Output

From the Output we can observe that on accessing or getting a single column separated from DataFrame its type gets converted to a Pandas Series type irrespective of the data type present in that series. On accessing the individual elements of the pandas Series we get the data is stored always in the form of numpy.datatype() either numpy.int64 or numpy.float64 or numpy.bool_ thus we observed that the Pandas data frame automatically typecast the data into the NumPy class format.

Example 2 :

Python3

# importing the module
import pandas as pd
  
# creating a DataFrame    
data = {'Name' : ['Jai', 'Princi', 'Gaurav', 'Anuj'],
        'Age' : [27, 24, 22, 32],
        'Address' : ['Delhi', 'Kanpur', 'Allahabad', 'Kannauj'],
        'Qualification' : ['Msc', 'MA', 'MCA', 'Phd']}
table = pd.DataFrame(data)
  
print("Data Types of The Columns in Data Frame")
display(table.dtypes)