How to Subtract Two Columns in Pandas DataFrame?
Last Updated :
19 Dec, 2021
In this article, we will discuss how to subtract two columns in pandas dataframe in Python.
Dataframe in use:
Method 1: Direct Method
This is the __getitem__ method syntax ([]), which lets you directly access the columns of the data frame using the column name.
Example: Subtract two columns in Pandas dataframe
Python3
import numpy as np
import pandas as pd
data = np.arange( 0 , 20 ).reshape( 4 , 5 )
df1 = pd.DataFrame(data,
index = [ 'Row 1' , 'Row 2' , 'Row 3' , 'Row 4' ],
columns = [ 'Column 1' , 'Column 2' , 'Column 3' ,
'Column 4' , 'Column 5' ])
df1[ 'Column 1' ] - df1[ 'Column 2' ]
|
Output:
Method 2: Defining a function
We can create a function specifically for subtracting the columns, by taking column data as arguments and then using the apply method to apply it to all the data points throughout the column.
Example: Subtract two columns in Pandas dataframe
Python3
import numpy as np
import pandas as pd
def diff(a, b):
return b - a
data = np.arange( 0 , 20 ).reshape( 4 , 5 )
df = pd.DataFrame(data,
index = [ 'Row 1' , 'Row 2' , 'Row 3' , 'Row 4' ],
columns = [ 'Column 1' , 'Column 2' , 'Column 3' ,
'Column 4' , 'Column 5' ])
df[ 'Difference_2_1' ] = df. apply (
lambda x: diff(x[ 'Column 2' ], x[ 'Column 2' ]), axis = 1 )
|
Output :
Method 3: Using apply()
Since the operation we want to perform is simple we can you can directly use the apply() method without explicitly defining a function. Provide the axis argument as 1 to access the columns.
Syntax:
s.apply(func, convert_dtype=True, args=())
Parameters:
- func: .apply takes a function and applies it to all values of pandas series.
- convert_dtype: Convert dtype as per the function’s operation.
- args=(): Additional arguments to pass to function instead of series.
Return Type: Pandas Series after applied function/operation.
Example: Subtract two columns in Pandas Dataframe
Python3
import pandas as pd
import numpy as np
data = np.arange( 0 , 20 ).reshape( 4 , 5 )
df = pd.DataFrame(data,
index = [ 'Row 1' , 'Row 2' , 'Row 3' , 'Row 4' ],
columns = [ 'Column 1' , 'Column 2' , 'Column 3' ,
'Column 4' , 'Column 5' ])
df[ 'diff_3_4' ] = df. apply ( lambda x: x[ 'Column 3' ] - x[ 'Column 4' ], axis = 1 )
df
|
Output:
assign() method assign new columns to a DataFrame, returning a new object (a copy) with the new columns added to the original ones.
Example: Subtract two columns in Pandas dataframe
Python3
import numpy as np
import pandas as pd
data = np.arange( 0 , 20 ).reshape( 4 , 5 )
df = pd.DataFrame(data,
index = [ 'Row 1' , 'Row 2' , 'Row 3' , 'Row 4' ],
columns = [ 'Column 1' , 'Column 2' , 'Column 3' ,
'Column 4' , 'Column 5' ])
df = df.assign(diff_1_5 = df[ 'Column 1' ] - df[ 'Column 5' ])
df
|
Output :
Like Article
Suggest improvement
Share your thoughts in the comments
Please Login to comment...