Analyzing Public Dataset on in Nigeria

Local Chapter Osun, Nigeria Chapter

Coordinated byNigeria ,

Kabirat Olayemi

Status: Completed

Project Duration: 23 Apr 2022 - 21 May 2022

Open Source resources available from this project

Github Repository

Project background.

Participation in data science in Nigeria has continually increased over the years. Students and graduates from various disciplines are fully captivated by data science potentials and are now gainfully engaged in the space. We have one major community in Nigeria who has taken over the task of tutoring undergraduate students in data science. This community naturally holds classes or bootcamps to introduce the basic data science tools such as python, R and databases. However, there is a big gap between learning and working on real-life datasets.

The problem.

In this four-week project, we seek to help upcoming data scientists learn and grow in the field by working on real-life datasets. They will learn how to collect, organize, and analyze different datasets directly about or related to Nigeria.

Project goals.

- To serve as a data repository about Nigeria.
- Provide visualization of multiple datasets in Nigeria.
- To help tell a story about occurrences in Nigeria.
- To serve as a tool for other researchers.
- Make results openly available on a website.

Project plan.

  • Week 1

    -Determine key websites that list datasets about Nigeria
    -Decide how to organise datasets, visualisations, and reports
    -Decide on a new dataset to create

  • Week 2

    -Start creating an index of datasets and websites that host them
    -Start creating visualisations and reports using the datasets in the index
    -Start scraping data for the new dataset

  • Week 3

    -Continue improving the index and creating visualizations
    -Start looking into ways to host the results
    -Organize new dataset and label it if necessary

  • Week 4

    -Finalize index and make sure it’s well-organized
    -Host visualizations and reports on a website
    -Finalize new dataset, host it and test it

Learning outcomes.

1. Learning how to search for, categorize and visualize datasets.

2. Learning how to use multiple datasets in one report to tell stories with data.

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