COVID-19数据集
包含2020年2月1日至4月5日全球各国COVID-19确诊病例和死亡病例的表格数据集,已预处理,适用于模型训练。

基本信息
资源简介
COVID-19数据集
【数据集背景】
本数据集源站标题为《sirreajohn/COVID-19-datasets》。源站首次发布:2020-04-19。
【数据内容】
源站原始描述:datasets country wise for data science models # COVID-19-datasets Datasets of confrimed cases and fatal-cases sorted country wise alphabetically ## Details of each country set: * All sets are preprocessed and ready to be used in training models.. * This data is from 1st feb 2020 to 5th april 2020 * The second index is to keep track of dates i.e index 12 suggests that it is day 12(12th feb 2020) from feb 1st 2020 - *This column is for day count - **This is for confirmed cases in that country till…
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://github.com/sirreajohn/COVID-19-datasets
使用许可:MIT。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
git clone https://github.com/sirreajohn/COVID-19-datasets.git
curl -L -o repo.zip https://github.com/sirreajohn/COVID-19-datasets/archive/refs/heads/master.zip
unzip repo.zip
源站 README 摘录(使用方式)
COVID-19-datasets
Datasets of confrimed cases and fatal-cases sorted country wise alphabetically
Details of each country set:
- All sets are preprocessed and ready to be used in training models…
- This data is from 1st feb 2020 to 5th april 2020
- The second index is to keep track of dates i.e index 12 suggests that it is day 12(12th feb 2020) from feb 1st 2020
- *This column is for day count
- **This is for confirmed cases in that country till April 5th 2020
- ***This is for fatal-cases in that country till April 5th 2020
- ****Index
references
- https://www.kaggle.com/c/covid19-global-forecasting-week-4/data
- https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series
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))
数据缺失?
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