Convert Floats to Integers in a Pandas DataFrame

Last Updated : 20 Aug, 2020

Let us see how to convert float to integer in a Pandas DataFrame. We will be using the astype() method to do this. It can also be done using the apply() method.

Method 1: Using DataFrame.astype() method

First of all we will create a DataFrame:

# importing the library
import pandas as pd
  
# creating a DataFrame
list = [['Anton Yelchin', 36, 75.2, 54280.20], 
        ['Yul Brynner', 38, 74.32, 34280.30], 
        ['Lev Gorn', 31, 70.56, 84280.50],
        ['Alexander Godunov', 34, 80.30, 44280.80], 
        ['Oleg Taktarov', 40, 100.03, 45280.30],
        ['Dmitriy Pevtsov', 33, 72.99, 70280.25], 
        ['Alexander Petrov', 42, 85.84, 25280.75]]
df = pd.DataFrame(list, columns =['Name', 'Age', 'Weight', 'Salary'])
display(df)

Output :

Example 1 : Converting one column from float to int using DataFrame.astype()

# displaying the datatypes
display(df.dtypes)
  
# converting 'Weight' from float to int
df['Weight'] = df['Weight'].astype(int)
  
# displaying the datatypes
display(df.dtypes)

Output :

Example 2: Converting more than one column from float to int using DataFrame.astype()

# displaying the datatypes
display(df.dtypes)
  
# converting 'Weight' and 'Salary' from float to int
df = df.astype({"Weight":'int', "Salary":'int'}) 
  
# displaying the datatypes
display(df.dtypes)

Output :

Method 2: Using DataFrame.apply() method

First of all we will create a DataFrame.

# importing the module
import pandas as pd
  
# creating a DataFrame
list = [[15, 2.5, 100.22], [20, 4.5, 50.21], 
        [25, 5.2, 80.55], [45, 5.8, 48.86], 
        [40, 6.3, 70.99], [41, 6.4, 90.25], 
        [51, 2.3, 111.90]]
df = pd.DataFrame(list, columns = ['Field_1', 'Field_2', 'Field_3'],
                  index = ['a', 'b', 'c', 'd', 'e', 'f', 'g'])
display(df)

Output :

Example 1: Converting a single column from float to int using DataFrame.apply(np.int64)

# importing the module
import numpy as np
  
# displaying the datatypes
display(df.dtypes)
  
# converting 'Field_2' from float to int
df['Field_2'] = df['Field_2'].apply(np.int64)
  
# displaying the datatypes
display(df.dtypes)

Output :

Example 2: Converting multiple columns from float to int using DataFrame.apply(np.int64)

# displaying the datatypes
display(df.dtypes)
  
# converting 'Field_2' and 'Field_3' from float to int
df['Field_2'] = df['Field_2'].apply(np.int64)
df['Field_3'] = df['Field_3'].apply(np.int64)
  
# displaying the datatypes
display(df.dtypes)

Output :

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes

Related Articles