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 :
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