How to use the DataFrame.mod() method in pandas

Overview

The DataFrame.mod() method from the pandas module is used to calculate the element-wise modulus (binary operator mod) of two DataFrames, Series, or Constants.

Note: We can also modulo operator % instead. However, it does not deal with empty NaN valuesfields.

Syntax

Parameters

It takes the following argument values:

other: This can be a DataFrame, Series, or Constant.
axis: This can be 0 or index or 1 or columns. Its default value is 'columns'.
level: The broadcast value across a level can either be int or None. Its default value is None.

fill_value: This can either be a float value or None. Its default value is None.

Return value

It returns a DataFrame containing modulo results.

Explanation

In the code snippet below, we'll calculate the modulus of:

DataFrame objectCallee object and argument constant value.
DataFrame object and argument DataFrame object.
DataFrame object and argument Series object.

# importing Pandas and Numpy
import pandas as pd
import numpy as np
# Creating a DataFrame
df1= pd.DataFrame([[5, 3, 6, 4],
				[11, None, 4, 3],
				[4, 3, 8, None],
				[5, 4, 2, 8]])
# Creating another DataFrame
df2= pd.DataFrame([[None, 4, 5, 9],
				[1, None, 4, 3],
				[14, 3, -1, None],
				[2, 14, 8, 8]])
# Creating Numpy array
data = np.array([6, 12, -3, 9])
# Converting to Python series
series = pd.Series(data)
"""DataFrame and Constant"""
# Invoking mod() method
# Evaluating modulus between df1 and constant
modulus= df1.mod(3, fill_value = 2)
# print results
print("DataFrame and Constant")
print(modulus)
"""Both are DataFrames"""
# Evaluating modulus between df1 and df2
modulus= df1.mod(df2, fill_value = 2)
print("\nBoth are DataFrames")
print(modulus)
"""DataFrame and Series"""
# Evaluating modulus between df1 and series
modulus= df1.mod(series)
print("\nDataFrame and Series")
print(modulus)