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Pandas can handle very large data sets and has a variety of functions and operations that can be applied to the data.

One of the simple operations is to subtract two columns and store the result in a new column, which we will discuss in this tutorial. This simple task can be done in many ways. We will calculate the difference between the 'a'and columns in the following DataFrame.'d'

import pandas as pd

df = pd.DataFrame(
    [[10, 6, 7, 8], [1, 9, 12, 14], [5, 8, 10, 6]], columns=["a", "b", "c", "d"]
)

print(df)

Output:

    a  b   c   d
0  10  6   7   8
1   1  9  12  14
2   5  8  10   6

Subtracting two columns in Pandas using __getitem__syntax ( )[]

The simplest way to subtract two columns is to access the desired column and create a new column using __getitem__the syntax ( ). For example:[]

import pandas as pd

df = pd.DataFrame(
    [[10, 6, 7, 8], [1, 9, 12, 14], [5, 8, 10, 6]], columns=["a", "b", "c", "d"]
)

df["d - a"] = df["d"] - df["a"]

print(df)

Output:

    a  b   c   d  d - a
0  10  6   7   8     -2
1   1  9  12  14     13
2   5  8  10   6      1

Subtracting Two Columns Using Functions in Pandas

We can easily create a function in Pandas to subtract two columns and apply()apply it to the specified columns of the DataFrame using the function. We will apply()provide the function with the argument axisand set it to 1, indicating that the function is applied to the column.

import pandas as pd

df = pd.DataFrame(
    [[10, 6, 7, 8], [1, 9, 12, 14], [5, 8, 10, 6]], columns=["a", "b", "c", "d"]
)


def x(a, b):
    return a - b


df["d - a"] = df.apply(lambda f: x(f["d"], f["a"]), axis=1)

print(df)

Output:

    a  b   c   d  d - a
0  10  6   7   8     -2
1   1  9  12  14     13
2   5  8  10   6      1

Since column subtraction is a relatively simple operation, we can directly use lambdathe keyword apply()to create a simple one-line function in the function.

import pandas as pd

df = pd.DataFrame(
    [[10, 6, 7, 8], [1, 9, 12, 14], [5, 8, 10, 6]], columns=["a", "b", "c", "d"]
)

df["d - a"] = df.apply(lambda x: x["d"] - x["a"], axis=1)

print(df)

Output:

    a  b   c   d  d - a
0  10  6   7   8     -2
1   1  9  12  14     13
2   5  8  10   6      1

assign()Subtracting two columns in Pandas using the

The DataFrame assign()method is used to add a column to a DataFrame after performing some operation. It returns a new DataFrame containing all the original and new columns. The following example will show how to assign()subtract two columns using the method.

import pandas as pd

df = pd.DataFrame(
    [[10, 6, 7, 8], [1, 9, 12, 14], [5, 8, 10, 6]], columns=["a", "b", "c", "d"]
)

df = df.assign(d_minus_a=df["d"] - df["a"])

print(df)

Output:

    a  b   c   d  d_minus_a
0  10  6   7   8         -2
1   1  9  12  14         13
2   5  8  10   6          1