Pandas: Calculate Percentage Change with pct_change()

Compute fractional or percentage changes between current and prior elements across Series and DataFrames using the pct_change() method. Track financial growth, calculate period-over-period variations, and configure lag periods.

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Introduction to pct_change() 🔝

The pct_change() method calculates the fractional change between the current element and a prior element (determined by the periods parameter). By default, it computes the change relative to the immediately preceding row (`periods=1`). The first row naturally results in `NaN`.

Create numerical sample series 🔝

We start with a monthly stock price or revenue Series to track sequential changes.

import pandas as pd

prices = pd.Series([100, 110, 105, 126], name="PRICE")
print(prices)
assert prices.shape == (4,)

Expected output

0    100
1    110
2    105
3    126
Name: PRICE, dtype: int64

Basic percentage change calculation 🔝

Call pct_change() on the Series to compute fractional changes relative to the prior row.

chg = prices.pct_change()
print(chg)
assert chg.iloc[1] == 0.1

Expected output

0    NaN
1    0.1
2   -0.045455
3    0.2
Name: PRICE, dtype: float64

Configuring lag periods 🔝

Use the periods parameter to compute changes across multiple rows (e.g., comparing current values against two periods prior).

chg_lag = prices.pct_change(periods=2)
print(chg_lag)
assert chg_lag.iloc[2] == 0.05

Expected output

0     NaN
1     NaN
2    0.05
3    0.145455
Name: PRICE, dtype: float64

Exercise: compute revenue growth 🔝

Given a Series rev = pd.Series([1000, 1200, 1500], name="REV"), compute the percentage change using default periods and verify that the final growth rate equals 0.25.

Exercise solution 🔝

Solution creating the Series and applying pct_change().

rev = pd.Series([1000, 1200, 1500], name="REV")
answer = rev.pct_change()
print(answer)
assert answer.iloc[2] == 0.25

Expected output

0    NaN
1    0.2
2    0.25
Name: REV, dtype: float64

Practice in Google Colab 🔝

Interactive Colab Notebook

Practice pct_change() examples interactively directly in your browser:

View on GitHub

Reference: Pandas pct_change() documentation.

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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