COVID19 Data Analysis Using Python

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このガイド付きプロジェクトでは、次のことを行います。

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
Intermediate中級
Cloudダウンロード不要
Video分割画面ビデオ
Comment Dots英語
Laptopデスクトップのみ

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.

あなたが開発するスキル

Python ProgrammingData AnalysisPandasSeabornStatistics

ステップバイステップで学習します

ワークエリアを使用した分割画面で再生するビデオでは、講師がこれらの手順を説明します。

  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.

ガイド付きプロジェクトの仕組み

ワークスペースは、ブラウザに完全にロードされたクラウドデスクトップですので、ダウンロードは不要です

分割画面のビデオで、講師が手順ごとにガイドします

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