Python | Pandas dataframe.sub()

DataFrame.sub() allows for element-wise subtraction between a DataFrame and another object, with added support for handling missing data. The DataFrame.sub() function is essentially equivalent to performing DataFrame - other, but with additional options to manage missing values in one of the inputs.

Syntax: DataFrame.sub(other, axis='columns', level=None, fill_value=None)

Parameters:

• other: A Series, DataFrame, or constant to subtract from the DataFrame.
• axis: Specifies the axis to align the subtraction on. For a Series input, this determines whether to match the Series index to the DataFrame columns (axis=1) or the rows (axis=0).
• level: Broadcasts the operation across a level, aligning Index values in a MultiIndex DataFrame.
• fill_value: Fills missing (NaN) values in either of the inputs before computation. If corresponding values in both inputs are missing, the result will also be missing.

The function returns a dataframe containing result of subtraction.

Example #1: Subtracting a Series from a DataFrame

Let’s use the sub() function to subtract the elements of a Series from the corresponding elements in a DataFrame.

Let's create the series 

Let's use the dataframe.sub() function for subtraction.

Output : 

Example #2: Subtracting One DataFrame from Another

In this example, we subtract the elements of one DataFrame from the corresponding elements in another DataFrame.

Output : 

Notice that each element in df1 has been subtracted from the corresponding element in df2.