COVID19 Data Analysis Using Python

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In this Guided Project, you will:

Learn the steps, needed to be taken to prepare your data sources for an analysis

Learn how to look at your data to find a good measure to stablish your analysis based upon

Learn to visualize the result of your analysis

Clock100 Minutes
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country. Notes: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Python ProgrammingData AnalysisPandasSeabornStatistics

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Importing COVID19 dataset and preparing it for the analysis by dropping columns and aggregating rows.

  2. Deciding on and calculating a good measure for our analysis.

  3. Merging two datasets and finding correlations among our data.

  4. Visualizing our analysis results using Seaborn.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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