Python or R for Data Analysis: Which Should You Learn?
February 4, 2025
Article
(1,961 reviews)
Recommended experience
Intermediate level
Learners should have familiarity with python programming language and having a little experience working with Jupyter notebook.
(1,961 reviews)
Recommended experience
Intermediate level
Learners should have familiarity with python programming language and having a little experience working with Jupyter notebook.
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
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Only available on desktop
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.
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.
Learners should have familiarity with python programming language and having a little experience working with Jupyter notebook.
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The Coursera Project Network is a select group of instructors who have demonstrated expertise in specific tools or skills through their industry experience or academic backgrounds in the topics of their projects. If you're interested in becoming a project instructor and creating Guided Projects to help millions of learners around the world, please apply today at teach.coursera.org.
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
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.
1,961 reviews
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Reviewed on Jul 30, 2020
This is very good this can help me in my personal project and my analysis in Data Science thank you coursera offer me this project as well as instructor of this project
Reviewed on Jun 12, 2020
This course is well structured I was going to give it 6 stars if I could see/download my written work. Otherwise, my expectations were sufficiently met.
Reviewed on Jul 5, 2020
The instructor's informative videos along with the facilitation of real time application of methods learnt through Rhyme made this a really worthwhile project.
Imperial College London
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Coursera Project Network
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University of California San Diego
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