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.
COVID19 Data Analysis Using Python
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4.5
(1,957 reviews)
Intermediate level
Recommended experience
100 Minutes
Learn at your own pace
Hands-on learning
What you'll learn
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
Skills you'll practice
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Taught in English
No downloads or installation required
Only available on desktop
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About this Guided Project
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:
Importing COVID19 dataset and preparing it for the analysis by dropping columns and aggregating rows.
Deciding on and calculating a good measure for our analysis.
Merging two datasets and finding correlations among our data.
Visualizing our analysis results using Seaborn.
Recommended experience
Learners should have familiarity with python programming language and having a little experience working with Jupyter notebook.
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Instructor ratings
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
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Follow along with pre-recorded videos from experts using a unique side-by-side interface.
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Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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