In this project, I assumed the role of a data analyst tasked with visualizing life expectancy and GDP data over time to uncover trends and regional differences. Throughout the project, I loaded and cleaned data, created and configured visualizations in order to provide insight about a) Life expectancy by year across each countries, and b) GDP Per Capita by Year across regions. Two visualizations will be created into a dashboard to gain insight about the dataset.
The Gapminder dataset SampleDataWS.csv combines data from multiple sources into coherent time-series information about life expectancy over time for countries and regions around the world.
Here are the steps I accomplished to complete this project:
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Import the life expectancy and GDP data into Power BI, using the csv file provided in this repository.
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Clean and transform the data for analysis. This involves using the Power QUery Editor to replace errors with null values, inserting year in appropriate columns, and change the data format of the relevant columns.
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Create interactive scatter plots and stacked column charts.
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Design an accessible report layout in Power BI, with inteactive elements and readible formatting.
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Customize visual markers and themes to enhance insights, such as placing the charts in vertical orientation for easier reading, and implementing color themes in order to clearly see insights and trends from different regions.
By the end of the project, I managed to create two charts using the data from the dataset provided. With this orientation, readers should be easy to gain insight from the two charts. A slicer was also available in the dashboard, allowing readers to quickly filter the regions they want to see.