This is a project which we do Covid-19 data collection and analysis according to the information from [a website](See the latest data in your region - Johns Hopkins Coronavirus Resource Center (jhu.edu)). The whole project is divided into three tasks, and detailed information will be shown below.

Our repository contains:

• Check: It's the most important part. There store our ordered final achievements of three tasks.
• Main: All of our codes, whether it's useful or not, are in this file, which may seems a little messy.
• Record: This file records our plans and notes. It's a record of our learning process.
• Pict: It includes our team logo.
• .DS_Store: It's a file that you can ignore it.
• .gitignore: It's a file can be ignored too, as its name.

• [Task 1](#task 1)

  • Introduction
  • What we learn in the task
  • What we do in the task
  • What we get in the task

• [Task 2](#task 2)

  • Introduction
  • What we learn in the task
  • What we do in the task
  • What we get in the task

• [Task 3](#task 3)

  • Introduction
  • What we learn in the task
  • What we do in the task
  • What we get in the task

• Contributing

In this task, we collect information about Covid-19 in American 52 states from a specific website, which is mentioned above, with a python crawler.

1. We learn how a website work, and according to which can we know the basic concept of crawling, and the basic way to crawl the data.
2. We learn to use two new python libraries, requests and json. We can simulate the operation of browser with library requests, so we may send a request to get data from web server and process the data in python with library json. Also, we learn further by coding the whole process of crawling into a function, which simplify the crawling greatly.

1. We collect infection, hospitalization and vaccination information in American52 states using the state_name.json provided, not hard coding.
2. We dispose the output using the library panda and we also learn to integrate all of the 52 tables into one, representing like a "3D chart", which enables us to analyze it more easily in the following tasks.

We finally get a file storing all the data crawled from the website in the form of a chart more than 3D, which includes many keys.

In this task, we do the data visualization with pyechart and control LED light to show some results in raspberryPi.

1. We learn how to use many python libraries: pyecharts, snapshot_selenium, phantomjs, imageio and so on.
2. We learn how to connect raspberry under many confusing situations, which is somehow one of the hardest part in this task.

1. We display the results in an American map which contains the data from 2020.1 till now in the form of gif.
2. We visualize the information of one state on raspberry and design a more complex result with binary encoding.

This project exists thanks to all the people who contributes

PROJECT MEMBER: @PlaneTraveller; @DDaname; @Mogranie

ADVISOR: @QLT;@ZCF