Spearman correlation in SciPy - Mini Project: Build & Apply

Calculate Spearman Correlation with SciPy

📖 Scenario: You are a data analyst working with two sets of related data points. You want to find out how strongly these two sets are related in terms of their rank order, not just their actual values.

🎯 Goal: Build a small Python program that calculates the Spearman correlation coefficient between two lists of numbers using the scipy library.

📋 What You'll Learn

Create two lists of numbers named data1 and data2 with exact values.

Create a variable named alpha to set the significance level.

Use scipy.stats.spearmanr to calculate the Spearman correlation coefficient and p-value.

Print the Spearman correlation coefficient and the p-value.

💡 Why This Matters

🌍 Real World

Spearman correlation is used when you want to measure how well two variables relate in terms of their order or rank, such as customer satisfaction rankings or survey responses.

💼 Career

Data analysts and scientists use Spearman correlation to find relationships in data that are not necessarily linear, helping in decision making and reporting.

1

Create the data lists

Create two lists called data1 and data2 with these exact values: data1 = [10, 20, 30, 40, 50] and data2 = [12, 24, 33, 47, 52].

SciPy

# Create the two data lists
# Your code here

Need a hint?

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

2

Set the significance level

Create a variable called alpha and set it to 0.05 to represent the significance level for the correlation test.

SciPy

data1 = [10, 20, 30, 40, 50]
data2 = [12, 24, 33, 47, 52]
# Create the alpha variable
# Your code here

Need a hint?

Use a simple assignment statement to create alpha.

3

Calculate Spearman correlation

Import spearmanr from scipy.stats. Then use spearmanr(data1, data2) to calculate the Spearman correlation coefficient and p-value. Store the results in variables called corr and p_value.

SciPy

data1 = [10, 20, 30, 40, 50]
data2 = [12, 24, 33, 47, 52]
alpha = 0.05
# Import spearmanr and calculate correlation and p-value
# Your code here

Need a hint?

Use from scipy.stats import spearmanr to import the function.

4

Print the Spearman correlation and p-value

Print the Spearman correlation coefficient stored in corr and the p-value stored in p_value using two separate print statements.

SciPy

from scipy.stats import spearmanr
data1 = [10, 20, 30, 40, 50]
data2 = [12, 24, 33, 47, 52]
alpha = 0.05
corr, p_value = spearmanr(data1, data2)
# Print the correlation and p-value
# Your code here

Need a hint?

Use print(corr) and print(p_value) to show the results.