Pandas: Calculate Statistical Mode with mode()

Compute the most common or frequently occurring values (modes) across Series or DataFrames using the Pandas mode() method. Handle multimodal distributions, find categorical or numerical modes, and manage missing values.

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Introduction to mode() 🔝

The mode() method calculates the value(s) that appear most frequently in a Series or DataFrame. Unlike mean() or median(), mode() always returns a Series or DataFrame to accommodate datasets with multiple tie values (multimodal distributions).

Create sample Series & DataFrame 🔝

We start with a numerical Series containing clear repeating values.

import pandas as pd

s = pd.Series([10, 20, 20, 30, 40], name="SCORES")
print(s)
assert s.shape == (5,)

Expected output

0    10
1    20
2    20
3    30
4    40
Name: SCORES, dtype: int64

Basic mode calculation 🔝

Call mode() on the Series to find its most frequent element.

m_val = s.mode()
print(m_val)
assert m_val.iloc[0] == 20

Expected output

0    20
dtype: int64

Handling multimodal data (multiple modes) 🔝

When multiple values share the highest frequency, mode() returns all of them ordered sequentially.

multi_s = pd.Series([10, 10, 20, 20, 30], name="VALS")
multi_mode = multi_s.mode()
print(multi_mode)
assert list(multi_mode) == [10, 20]

Expected output

0    10
1    20
dtype: int64

Exercise: compute categorical mode 🔝

Given a Series fruits = pd.Series(["apple", "banana", "apple", "cherry", "banana", "apple"], name="FRUIT"), compute its mode using mode() and verify that the first mode equals "apple".

Exercise solution 🔝

Solution creating the Series and calculating mode().

fruits = pd.Series(["apple", "banana", "apple", "cherry", "banana", "apple"], name="FRUIT")
answer = fruits.mode()
print(answer)
assert answer.iloc[0] == "apple"

Expected output

0    apple
dtype: object

Practice in Google Colab 🔝

Interactive Colab Notebook

Practice mode() examples interactively directly in your browser:

View on GitHub

Reference: Pandas mode() documentation.

Subhendu Mohapatra

Author & Instructor at plus2net

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