Descriptive statistics review in Data Analysis Python - Mini Project: Build & Apply

Descriptive statistics review

📖 Scenario: You work as a data analyst for a small retail store. You have collected daily sales data for a week. Your manager wants you to summarize this data to understand the sales performance.

🎯 Goal: You will create a list of daily sales, set a threshold for high sales, filter the sales above this threshold, and then calculate basic descriptive statistics like mean and median for these high sales.

📋 What You'll Learn

Create a list called daily_sales with exact values for 7 days

Create a variable called high_sales_threshold with the value 200

Use a list comprehension to create a list called high_sales containing sales greater than high_sales_threshold

Calculate the mean and median of high_sales using the statistics module

Print the mean and median values exactly as shown

💡 Why This Matters

🌍 Real World

Retail stores and many businesses collect daily sales data. Summarizing this data helps managers understand performance and make decisions.

💼 Career

Data analysts often need to clean, filter, and summarize data using descriptive statistics to provide insights to stakeholders.

1

Create the daily sales data

Create a list called daily_sales with these exact values: [150, 220, 180, 300, 250, 90, 400]

Data Analysis Python

# Create the list daily_sales with the given values
# Your code here

Hint

Use square brackets to create a list and separate the numbers with commas.

2

Set the high sales threshold

Create a variable called high_sales_threshold and set it to 200

Data Analysis Python

daily_sales = [150, 220, 180, 300, 250, 90, 400]
# Create the variable high_sales_threshold and set it to 200
# Your code here

Hint

Just assign the number 200 to the variable high_sales_threshold.

3

Filter high sales using list comprehension

Use a list comprehension to create a list called high_sales that contains only the sales from daily_sales greater than high_sales_threshold

Data Analysis Python

daily_sales = [150, 220, 180, 300, 250, 90, 400]
high_sales_threshold = 200
# Create the list high_sales using list comprehension
# Your code here

Hint

Use the syntax: [item for item in list if condition].

4

Calculate and print mean and median of high sales

Import the statistics module. Calculate the mean and median of high_sales using statistics.mean() and statistics.median(). Then print the results exactly as: Mean: <mean_value> and Median: <median_value>

Data Analysis Python

daily_sales = [150, 220, 180, 300, 250, 90, 400]
high_sales_threshold = 200
high_sales = [sale for sale in daily_sales if sale > high_sales_threshold]
# Import statistics and calculate mean and median of high_sales
# Print the mean and median values
# Your code here

Hint

Use import statistics at the top. Then use statistics.mean(high_sales) and statistics.median(high_sales). Use f-strings to print.