Dataframe data types – How to get & check data types of Dataframe columns in Python Pandas

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How to get & check data types of dataframes columns in python pandas ?

Dataframe data types: In this article we will discuss different ways to get the data type of single or multiple columns.

Use Dataframe.dtype to get data types of columns in Dataframe :

In python’s pandas module provides Dataframe class as a container for storing and manipulating two-dimensional data which provides an attribute to get the data type information of each column.

This Dataframe.dtype returns a series mentioned with the data type of each column.

Let’s try with an example:

#Program :

import pandas as pd
import numpy as np
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
   ('anjali',28,'agra','dog','lily'),
   ('tia',42,'jaipur','elephant','lotus'),
   ('kapil',51,'patna','cow','tulip'),
   ('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])
print(df)
Output:
     Name   Age     Place     Animal     Flower
a    riya      37        delhi       cat          rose
b   anjali    28        agra       dog          lily
c     tia      42        jaipur    elephant     lotus
d   kapil    51       patna       cow          tulip
e     raj      30     banglore     lion       orchid

This is the contents of the dataframe. Now let’s fetch the data types of each column in dataframe.

#Program :

import pandas as pd
import numpy as np
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
   ('anjali',28,'agra','dog','lily'),
   ('tia',42,'jaipur','elephant','lotus'),
   ('kapil',51,'patna','cow','tulip'),
   ('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])
DataType = df.dtypes
print('Data type of each column:')
print(DataType)
Output:
Data type of each column:
Name      object
Age          int64
Place       object
Animal    object
Flower    object
dtype:     object

Get Data types of dataframe columns as dictionary :

#Program :

import pandas as pd
import numpy as np
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
   ('anjali',28,'agra','dog','lily'),
   ('tia',42,'jaipur','elephant','lotus'),
   ('kapil',51,'patna','cow','tulip'),
   ('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])
#get a dictionary containing the pairs of column names and data types object
DataTypeDict = dict(df.dtypes)
print('Data type of each column :')
print(DataTypeDict)
Output:
Data type of each column  :{'Name': dtype('O'), 'Age': dtype('int64'), 'Place': dtype('O'), 'Animal': dtype('O'), 'Flower': dtype('O')}

Get the data type of a single column in dataframe :

By using Dataframe.dtypes we can also get the data type of a single column from a series of objects.

#Program :

import pandas as pd
import numpy as np
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
   ('anjali',28,'agra','dog','lily'),
   ('tia',42,'jaipur','elephant','lotus'),
   ('kapil',51,'patna','cow','tulip'),
   ('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])
#get a dictionary containing the pairs of column names and data types object
DataTypeObj = df.dtypes['Age']
print('Data type of each column Age : ')
print(DataTypeObj)
Output :
Data type of each column Age :int64

Get list of pandas dataframe column names based on data types :

Suppose, we want a list of column names based on datatypes. Let’s take an example program whose data type is object(string).

import pandas as pd
import numpy as np
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
('anjali',28,'agra','dog','lily'),
('tia',42,'jaipur','elephant','lotus'),
('kapil',51,'patna','cow','tulip'),
('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])

# Get  columns whose data type is object means string
filteredColumns = df.dtypes[df.dtypes == np.object]
# list of columns whose data type is object means string
listOfColumnNames = list(filteredColumns.index)
print(listOfColumnNames)
Output:
['Name', 'Place', 'Animal', 'Flower']

Get data types of a dataframe using Dataframe.info() :

Dataframe.info() function is used to get simple summary of a dataframe. By using this method we can get information about a dataframe including the index dtype and column dtype, non-null values and memory usage.

#program :

import pandas as pd
import numpy as np
#list of tuples
game = [('riya',37,'delhi','cat','rose'),
('anjali',28,'agra','dog','lily'),
('tia',42,'jaipur','elephant','lotus'),
('kapil',51,'patna','cow','tulip'),
('raj',30,'banglore','lion','orchid')]
#Create a dataframe object
df = pd.DataFrame(game, columns=['Name','Age','Place','Animal','Flower'], index=['a','b','c','d','e'])
df.info()
Output:
<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, a to e
Data columns (total 5 columns): 
#   Column  Non-Null Count  Dtype 
---  ------  --------------  -----  
a   Name     5 non-null      object 
b   Age        5 non-null      int64  
c   Place      5 non-null      object 
d   Animal   5 non-null      object 
e   Flower   5 non-null      object
dtypes: int64(1), object(4)
memory usage: 240.0+ bytes