Novel Corona Virus 2019 Dataset（新型冠状病毒2019年数据集）

Novel Corona Virus 2019 Dataset（新型冠状病毒2019年数据集）

原文：

Novel Corona Virus 2019 Dataset

Day level information on covid-19 affected cases

From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.

So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.

Johns Hopkins University has made an excellent dashboard using the affected cases data. Data is extracted from the google sheets associated and made available here.

Edited:

Now data is available as csv files in the Johns Hopkins Github repository. Please refer to the github repository for the Terms of Use details. Uploading it here for using it in Kaggle kernels and getting insights from the broader DS community.

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.

译：

新型冠状病毒2019数据集

covid-19感染病例的日水平信息

来自世界卫生组织-2019年12月31日，世卫组织接到中国湖北省武汉市多起肺炎病例的警报。该病毒与其他已知病毒不匹配。这引起了人们的关注，因为当病毒是新病毒时，我们不知道它如何影响人类。

因此，当向更广泛的数据科学界提供有关受影响人群的日常信息时，可以提供一些有趣的见解。

约翰霍普金斯大学利用受影响病例的数据制作了一个很好的仪表盘。数据是从google表格中提取出来的，并在这里提供。

编辑时间：

现在数据以csv文件的形式存在于Johns Hopkins Github存储库中。有关使用条款的详细信息，请参阅github存储库。上传到这里，以便在Kaggle内核中使用它，并从更广泛的DS社区获得见解。

2019新型冠状病毒（2019 nCoV）是一种病毒（更具体地说，冠状病毒），被确定为呼吸道疾病爆发的原因，首次在中国武汉发现。早些时候，据报道，在中国武汉爆发的疫情中，许多患者与一个大型海鲜和动物市场有某种联系，这表明动物与人之间的传播。然而，据报道，越来越多的病人没有接触过动物市场，这表明人与人之间的传播正在发生。目前，尚不清楚这种病毒在人与人之间传播的容易程度和可持续性。

该数据集包含2019年新型冠状病毒感染病例数、死亡人数和恢复情况的每日信息。请注意，这是一个时间序列数据，因此任何一天的病例数都是累计数。

数据可从2020年1月22日获得。

列说明

这个数据集中的主文件是covid_19_数据.csv具体描述如下。

版权声明：本文内容由网络用户投稿，版权归原作者所有，本站不拥有其著作权，亦不承担相应法律责任。如果您发现本站中有涉嫌抄袭或描述失实的内容，请联系我们jiasou666@gmail.com 处理，核实后本网站将在24小时内删除侵权内容。