How to Subtract Two Columns in Pandas DataFrame

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You can use the following syntax to subtract one column from another in a pandas DataFrame:

#subtract column 'B' from column 'A'
df['A-B'] = df.A- df.B

The following examples show how to use this syntax in practice.

Example 1: Subtract Two Columns in Pandas

The following code shows how to subtract one column from another in a pandas DataFrame and assign the result to a new column:

import pandas as pd

#create DataFrame 
df = pd.DataFrame({'A': [25, 12, 15, 14, 19, 23, 25, 29],
                   'B': [5, 7, 8, 9, 12, 9, 12, 4],
                   'C': [11, 8, 10, 6, 6, 5, 9, 12]})

#subtract column B from column A
df['A-B'] = df.A - df.B

#view DataFrame
df

        A	B	C	A-B
0	25	5	11	20
1	12	7	8	5
2	15	8	10	7
3	14	9	6	5
4	19	12	6	7
5	23	9	5	14
6	25	12	9	13
7	29	4	12	25

The new column called ‘A-B‘ displays the results of subtracting the values in column B from the values in column A.

Example 2: Subtract Two Columns with Missing Values

If we subtract one column from another in a pandas DataFrame and there happen to be missing values in one of the columns, the result of the subtraction will always be a missing value:

import pandas as pd
import numpy as np

#create DataFrame with some missing values
df = pd.DataFrame({'A': [25, 12, 15, 14, 19, 23, 25, 29],
                   'B': [5, 7, np.nan, 9, 12, np.nan, 12, 4],
                   'C': [np.nan, 8, 10, 6, 6, 5, 9, 12]}) 

#subtract column B from column A
df['A-B'] = df.A - df.B

#view DataFrame
df

	A	B	C	A-B
0	25	5.0	NaN	20.0
1	12	7.0	8.0	5.0
2	15	NaN	10.0	NaN
3	14	9.0	6.0	5.0
4	19	12.0	6.0	7.0
5	23	NaN	5.0	NaN
6	25	12.0	9.0	13.0
7	29	4.0	12.0	25.0

If you’d like, you can replace all of the missing values in the dataFrame with zeros using the df.fillna(0) function before subtracting one column from another:

import pandas as pd
import numpy as np

#create DataFrame with some missing values
df = pd.DataFrame({'A': [25, 12, 15, 14, 19, 23, 25, 29],
                   'B': [5, 7, np.nan, 9, 12, np.nan, 12, 4],
                   'C': [np.nan, 8, 10, 6, 6, 5, 9, 12]}) 

#replace all missing values with zeros
df = df.fillna(0)

#subtract column B from column A
df['A-B'] = df.A - df.B

#view DataFrame
df
	A	B	C	A-B
0	25	5.0	0.0	20.0
1	12	7.0	8.0	5.0
2	15	0.0	10.0	15.0
3	14	9.0	6.0	5.0
4	19	12.0	6.0	7.0
5	23	0.0	5.0	23.0
6	25	12.0	9.0	13.0
7	29	4.0	12.0	25.0

Additional Resources

How to Add Rows to a Pandas DataFrame
How to Add a Numpy Array to a Pandas DataFrame
How to Count Number of Rows in Pandas DataFrame