Skip to content

StatSquid

Squid-Speed Stats: The Good, the Bad, and the Gaussian

sales data analyis

Sales Data Analysis in Action: A Case Study with NumPy and pandas

Posted on September 10, 2025September 15, 2025 By squid_admin No Comments on Sales Data Analysis in Action: A Case Study with NumPy and pandas

This data project has been used as a take-home assignment in the recruitment process for the data science positions at 23andMe.

Assignment
Please answer the questions below based on the data provided:

Plot daily sales for all 50 weeks.

It looks like there has been a sudden change in daily sales. What date did it occur?

Is the change in daily sales at the date you selected statistically significant? If so, what is the p-value?

Does the data suggest that the change in daily sales is due to a shift in the proportion of male-vs-female customers? Please use plots to support your answer (a rigorous statistical analysis is not necessary).

Assume a given day is divided into four dayparts:

night (12:00AM – 6:00AM),
morning (6:00AM – 12:00PM),
afternoon (12:00PM – 6:00PM),
evening (6:00PM – 12:00AM).
What is the percentage of sales in each daypart over all 50 weeks?

Data Description
The datasets/ directory contains fifty CSV files (one per week) of timestamped sales data. Each row in a file has two columns:

sale_time – The timestamp on which the sale was made e.g. 2012-10-01 01:42:22
purchaser_gender – The gender of the person who purchased (male or female)
Practicalities
Please work on the questions in the displayed order. Make sure that the solution reflects your entire thought process – it is more important how the code is structured rather than the final answers. You are expected to spend no more than 1-2 hours solving this project.

Numpy-Pandas Tags:data analysis case study, learn numpy and pandas, nump and pandas, sales data analysis

Post navigation

Previous Post: Learning Python for DA: Not Just Functions, But Frameworks for Thinking
Next Post: Independence & Dependence: Probability’s Control Flow

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

  • Learning
  • Maths for Machine Learning
  • Numpy-Pandas
  • Probability
  • September 2025
September 2025
M T W T F S S
1234567
891011121314
15161718192021
22232425262728
2930  
     

Copyright © 2025 StatSquid.

Powered by PressBook Masonry Blogs

Powered by
...
►
Necessary cookies enable essential site features like secure log-ins and consent preference adjustments. They do not store personal data.
None
►
Functional cookies support features like content sharing on social media, collecting feedback, and enabling third-party tools.
None
►
Analytical cookies track visitor interactions, providing insights on metrics like visitor count, bounce rate, and traffic sources.
None
►
Advertisement cookies deliver personalized ads based on your previous visits and analyze the effectiveness of ad campaigns.
None
►
Unclassified cookies are cookies that we are in the process of classifying, together with the providers of individual cookies.
None
Powered by