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This challenge is to test data aptitude and an ability to write efficient Python

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ELSA Product Analyst Challenge

A very important thing we do in ELSA is following user trends and patterns, so that we can quickly adapt our product to changes and new arising opportunities.

Objective

Create a dashboard with meaningful insights for the given data, followed by an explanatory report.

Tasks

  • Download the data csv from here

  • Clean and prepare the data in Python (can be a simple script or notebook)

  • Choose the most relevant metrics and insights

  • Create the dashboard, in a technology of your choice (Tableau, Google Data Studio, etc), presenting the chosen metrics

  • Write a small report detailing any findings you deem important

Data

The data is provided in a csv file and contains the population count for different countries and cities over some years. Data columns are self explanatory.

Deliverables

  • The cleaning and preparation Python code/script
  • Dashboard link/access
  • Simple report of the challenge solution and results obtained
  • Any other relevant information you deem important

Edit by Edgar on Nov 27

Python cleaning script is available in the notebook: Exploratory Data Analysis and Cleaning.ipynb Populations_data_exploratory_profile.html is a on exploratory profile of the whole dataset before cleaning. Interactive report is available here.

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This challenge is to test data aptitude and an ability to write efficient Python

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