Correlation (correlate) in SciPy - Mini Project: Build & Apply

Calculate Correlation Using scipy.correlate

📖 Scenario: You are analyzing two simple time series data sets representing daily sales of two products in a small store. You want to find how these two sales patterns relate to each other by calculating their correlation.

🎯 Goal: Build a Python program that uses scipy.correlate to find the correlation between two lists of sales data.

📋 What You'll Learn

Create two lists named sales_product_a and sales_product_b with exact daily sales values.

Create a variable named mode with the value 'full' to configure the correlation.

Use scipy.correlate with sales_product_a, sales_product_b, and mode to calculate the correlation and store it in correlation_result.

Print the correlation_result to see the correlation values.

💡 Why This Matters

🌍 Real World

Correlation helps find relationships between two sets of data, like sales of two products over time, to understand if they move together.

💼 Career

Data scientists and analysts use correlation to find patterns and connections in data, which helps businesses make better decisions.

1

Create sales data lists

Create two lists called sales_product_a and sales_product_b with these exact values: sales_product_a = [10, 20, 30, 40, 50] and sales_product_b = [15, 25, 35, 45, 55].

SciPy

# Create the sales data lists
# Your code here

Need a hint?

Use square brackets to create lists and separate numbers with commas.

2

Set correlation mode

Create a variable called mode and set it to the string 'full' to specify the correlation mode.

SciPy

sales_product_a = [10, 20, 30, 40, 50]
sales_product_b = [15, 25, 35, 45, 55]
# Create the mode variable
# Your code here

Need a hint?

Assign the string 'full' to the variable mode.

3

Calculate correlation using scipy.correlate

Import correlate from scipy.signal. Then use correlate with sales_product_a, sales_product_b, and mode to calculate the correlation. Store the result in a variable called correlation_result.

SciPy

sales_product_a = [10, 20, 30, 40, 50]
sales_product_b = [15, 25, 35, 45, 55]
mode = 'full'
# Import correlate and calculate correlation_result
# Your code here

Need a hint?

Use from scipy.signal import correlate to import. Then call correlate() with the two lists and the mode.

4

Print the correlation result

Write a print statement to display the value of correlation_result.

SciPy

from scipy.signal import correlate

sales_product_a = [10, 20, 30, 40, 50]
sales_product_b = [15, 25, 35, 45, 55]
mode = 'full'

correlation_result = correlate(sales_product_a, sales_product_b, mode=mode)
# Print the correlation_result
# Your code here

Need a hint?

Use print(correlation_result) to show the correlation values.