COVID-19数据集
整合多个COVID-19报告数据的统一数据集，包含Report_Data字段以跟踪时间框架。
基本信息
资源简介
该项目收集并整合来自不同报告的不同数据集，形成一个统一的数据集。数据集基于最新版本，所有信息集中在一个文件中，包含Report_Data字段以跟踪时间框架。
下载信息
注册下载
Tips: 该数据集需要在对应的数据源网站注册通过后，才能进行数据下载，注册有对应要求，或者需要收费。
暂未开放公开下载
Tips: 该数据集属于公开下载，应该可以免费公开下载。
免登录有偿下载
Tips: 该数据集 Qianfanghub 可以协助提供有偿下载服务，注意，服务不针对数据相关产权，只是技术服务费。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放千方医数集，医疗数据集部分，是为社区服务的公开医疗数据集搜索引擎，并不存储或者下载原始的任何数据。 如果您有其他医疗数据需求，可以和客服联系，或者下工单。我们有强大的三甲医疗机构帮助您提供个性化的医疗数据定制、采集、标注服务。
使用方式
数据集获取
git clone https://github.com/waldirio/covid-19_dataset.git
curl -L -o repo.zip https://github.com/waldirio/covid-19_dataset/archive/refs/heads/master.zip
unzip repo.zip
源站 README 摘录（使用方式）
covid-19_dataset
The main idea of this project is to collect the data shared on the link below and create a single dataset, combining all the availables reports in different schemas.
https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_daily_reports
At the end, the schema is based on the latest version and the whole information will be available in a single file. Also, another great improvement, there is a single column Report_Data where this field will be responsible for keep the timeframe track. This is better because we can keep the current number of columns and add new information with no impact.
Here we can see a simple snippet
Report_Data,FIPS,Admin2,Province_State,Country_Region,Last_Update,Lat,Long_,Confirmed,Deaths,Recovered,Active,Combined_Key
01-22-2020,,,Anhui,Mainland China,1/22/2020 17:00,,,1,,,,
01-22-2020,,,Beijing,Mainland China,1/22/2020 17:00,,,14,,,,
01-22-2020,,,Chongqing,Mainland China,1/22/2020 17:00,,,6,,,,
...
03-24-2020,27011,Big Stone,Minnesota,US,2020-03-24 23:37:31,45.42712824,-96.41403739,1,0,0,0,"Big Stone, Minnesota, US"
03-24-2020,38007,Billings,North Dakota,US,2020-03-24 23:37:31,47.02366884,-103.3762965,0,0,0,0,"Billings, North Dakota, US"
03-24-2020,16011,Bingham,Idaho,US,2020-03-24 23:37:31,43.21672879999999,-112.3978437,2,0,0,0,"Bingham, Idaho, US"
...
03-29-2020,,,,West Bank and Gaza,2020-03-29 23:08:13,31.9522,35.2332,109,1,18,90,West Bank and Gaza
03-29-2020,,,,Zambia,2020-03-29 23:08:13,-13.133897,27.849332,29,0,0,29,Zambia
03-29-2020,,,,Zimbabwe,2020-03-29 23:08:13,-19.015438,29.154857,7,1,0,6,Zimbabwe
Ps.: The python version used was 3.7, however, you probably will be able to run on python 2.6 as well.
To run, just clone the code and execute as below
$ ./covid-19_dataset.py
Link: https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_daily_reports
01-22-2020.csv
01-23-2020.csv
01-24-2020.csv
01-25-2020.csv
01-26-2020.csv
...
03-27-2020.csv
03-28-2020.csv
03-29-2020.csv
Saving to file: covid_final_timeframe.csv
Hope you enjoy this dataset.
Be Safe
Waldirio
数据加载示例（表格/文本类）
import pandas as pd, glob, os
files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))
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