Data Analysis exercises

This project aims to help you train Data Analysis skills and build a small portfolio.

Using the data for the Seattle Library Checkout Records complete the following tasks.

How to start:

1. fork this repo
2. download the data and place it in a folder called data inside this project
3. create a jupyter notebook file for each task (recommended)
4. create a markdown file to answer each task (reports can be delivered any way you want)

Simple questions

Task

In this first task, answer the following questions using the datasets:

• how many books were checkout in 2017?
• how many books are there in the library? how many titles?
• what are the top 10 loaned books in 2017?
• how many books titles were taken on loan in 2017?
• what was the most popular genre in 2017?
• did the number of book loans diminished or increased from 2016 to 2017? By how much?

Expected learning outcomes

To successfully complete this task, you shall be able to:

• demonstrate familiarity with simple data manipulation
• demonstrate awareness of how to join multiple datasets
• demonstrate the ability of performing operations on a dataset

Exploratory data analysis

Task

Create a report for the library directing board outlining the behaviour of the library's users.

Expected learning outcomes

At the completion of this task, it is expected that you are able to:

• demonstrate the ability of exploring a dataset
• demonstrate the ability to interpret the data and translate it to a non technical audience

Qualitative research

Task

Based on your findings in the previous task, create a qualitative research proposal. The proposal will be delivered to the directing board in order to obtain fundings for the research.

Expected learning outcomes

To successfully complete this task, you shall be able to:

• demonstrate the ability to further explore the topic and generate a more in depth qualitative research