COVID19 Data Analysis Using Python
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
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
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.
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
Reviews
TOP REVIEWS FROM COVID19 DATA ANALYSIS USING PYTHON
This course is very good for beginners, although it misses out a lot of points in terms of professional data analysis... Still, if you are a beginner, you will benefit a lot from this course!
Very Informative. You do not have to know a lot of Programming to follow along, just a bit of basic should be Enough. Concepts are very well explained and the course is just at the right pace.
i guess it is a fun course ad very easily managed via rhyme notebook. i guess anyone with interest in data science can come here and catch some curiosity or understand what they need to learn.
Well structured, easy to understand and step by step guide. I really enjoyed working on this project. If one graded practical assignment is included in this project, it would be much better.
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