新型冠状病毒2019数据集
每日累计的新型冠状病毒肺炎确诊病例、死亡和康复时间序列数据集。

基本信息
资源简介
新型冠状病毒2019数据集
【数据集背景】
本数据集源站标题为《indrajeetapache/Novel-Corona-Virus-2019-Dataset》。源站首次发布:2020-03-22。
【数据内容】
源站原始描述:Novel Corona Virus 2019 Dataset Kaggle # Novel-Corona-Virus-2019-Dataset Novel Corona Virus 2019 Dataset Kaggle Content 2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients repor…
【适用方向】
时序数据适用于疾病进展预测、生理信号监测与事件发生的时序建模。
【获取与许可】
源站页面:https://github.com/indrajeetapache/Novel-Corona-Virus-2019-Dataset
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/indrajeetapache/Novel-Corona-Virus-2019-Dataset.git
curl -L -o repo.zip https://github.com/indrajeetapache/Novel-Corona-Virus-2019-Dataset/archive/refs/heads/master.zip
unzip repo.zip
源站 README 摘录(使用方式)
Novel-Corona-Virus-2019-Dataset
Novel Corona Virus 2019 Dataset Kaggle
Content
2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC
This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.
The data is available from 22 Jan, 2020.
Column Description
Main file in this dataset is covid_19_data.csv and the detailed descriptions are below.
covid_19_data.csv
Sno - Serial number
ObservationDate - Date of the observation in MM/DD/YYYY
Province/State - Province or state of the observation (Could be empty when missing)
Country/Region - Country of observation
Last Update - Time in UTC at which the row is updated for the given province or country. (Not standardised and so please clean before using it)
Confirmed - Cumulative number of confirmed cases till that date
Deaths - Cumulative number of of deaths till that date
Recovered - Cumulative number of recovered cases till that date
2019_ncov_data.csv
This is older file and is not being updated now. Please use the covid_19_data.csv file
Added two new files with individual level information
COVID_open_line_list_data.csv
This file is obtained from this link
COVID19_line_list_data.csv
This files is obtained from this link
Country level datasets
If you are interested in knowing country level data, please refer to the following Kaggle datasets:
India - https://www.kaggle.com/sudalairajkumar/covid19-in-india
South Korea - https://www.kaggle.com/kimjihoo/coronavirusdataset
Italy - https://www.kaggle.com/sudalairajkumar/covid19-in-italy
Brazil - https://www.kaggle.com/unanimad/corona-virus-brazil
USA - https://www.kaggle.com/sudalairajkumar/covid19-in-usa
Switzerland - https://www.kaggle.com/daenuprobst/covid19-cases-switzerland
Indonesia -
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))
完整仓库:github.com/indrajeetapache/Novel-Corona-Virus-2019-Dataset
数据缺失?
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