Data Analysis: Sales from an Electronic Store

A data analysis project of the sales dataset from an electronic store using tools like Python and Flourish.

Daniel Querales

Project overview

  • This is a data analysis project of the sales records from an electronic store.
  • Sales were evaluated by products, city and time.
  • The project was made for educational purpose.
  • The tools used are Python (Pandas and Numpy) and Flourish.
  • All the files can be downloaded from my GitHub Repository.

Objectives

The goal is to build a report that shows how was the sales from an electronics store to know what needs to do to increase its profits

Data transformation and data preparation

Importing data

All the data was obtained from multiples .csv, one for each month, imported to a Jupyter Notebook, then cleaned and prepared for analysis.

Asking the Questions

a) How much was the total sales amount?

b) Which months had the highest sales?

c) Which day of the week was the best performer?

d) What is the best hour to sell our products?

e) How was our sales by city?

f) Which are our most popular items sold?

g) Which items are often sold together?

Conclusions

  • The total sales was around 35M of dollars.
  • October and December are the best selling months.
  • Tuesday was the best performer for sales.
  • The best times to sell are at 12:00 and 19:00.
  • Sales in California were much higher than in the other states.
  • The most popular item sold was the Macbook Pro Laptop.
  • Phones, headphones and USB-C cables are usually sold together.