Case study from Google Professional Data Analytics Certificate, however this version is a python implementation, the SQL or R version is in work.
Scenerio: The role of the analyzer is a junior data analyst, who is working in the marketing analyst team at Cyclistic, a bike-share company in Chicago. The director of marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore, your team wants to understand how casual riders and annual members use Cyclistic bikes dierently. From these insights, your team will design a new marketing strategy to convert casual riders into annual members. But first, Cyclistic executives must approve your recommendations, so they must be backed up with compelling data insights and professional data visualizations.
Background: Cyclistic’s finance analysts have concluded that annual members are much more profitable than casual riders. Although the pricing flexibility helps Cyclistic attract more customers, Moreno believes that maximizing the number of annual members will be key to future growth. Rather than creating a marketing campaign that targets all-new customers, Moreno believes there is a very good chance to convert casual riders into members. She notes that casual riders are already aware of the Cyclistic program and have chosen Cyclistic for their mobility needs. Moreno has set a clear goal: Design marketing strategies aimed at converting casual riders into annual members. In order to do that, however, the marketing analyst team needs to better understand how annual members and casual riders dier, why casual riders would buy a membership, and how digital media could aect their marketing tactics. Moreno and her team are interested in analyzing the Cyclistic historical bike trip data to identify trends.
For the case the data analyst is supposed to answer only:
How do annual members and casual riders use Cyclistic bikes differently?
I used python notebook Google Colab to clean, organize and join data. Further a pandas pivot table was used to summerize the results.