strata_sales-data-analysis

stratascratch data project assignment_link

Sales Data Analysis

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

Assignment

EDA

Please answer the questions below based on the data provided:

1. Plot daily sales for all 50 weeks.
2. It looks like there has been a sudden change in daily sales. What date did it occur?
3. Is the change in daily sales at the date you selected statistically significant? If so, what is the p-value?
4. 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).
5. 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.

Project setup

• first create a repo on github
  • include a README.md file
  • include .gitignore file (python based template)
• then clone the repo to a local directory
• cd into the cloned directory
• create the following
  • a practise jupyter notebook
  • requirements.txt
  • Makefile
• create a virtual environment python3 -m venv venv
• activate the venv source venv/bin/activate
• open the notebook to start the work (prefer PyCharm for this project)
  • read all the instructions first from the URL

Project approach

• load the data