纽约市COVID-19数据集
纽约市COVID-19流行病学表格数据集，包含检测、阳性、住院和死亡数据。
基本信息
资源简介
该数据集来自纽约市开放数据存储库，由卫生与心理卫生部门提供。数据包含通过样本采集日期定义的队列的COVID-19检测结果，包括确诊病例、住院和死亡人数，以表格形式呈现，用于流行病学监测和趋势分析。
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
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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/ritawang917/Covid-19-Group-Project.git
curl -L -o repo.zip https://github.com/ritawang917/Covid-19-Group-Project/archive/refs/heads/main.zip
unzip repo.zip
源站 README 摘录（使用方式）
Covid-19
Selected Topic-Covid-19
Purpose of the Project
The novel coronavirus disease (COVID-19) is an infectious disease caused by SARS-CoV-2 which is a type of coronavirus discovered in 2019. Coronavirus pandemic was originated from China in December 2019, has resulted with over 604 Million cases and 6.5 Million deaths worldwide. With Covid-19 pandemic, we are in a world crisis likes of which hasn’t been seen in 100 years.The enormous scale of the crisis and the impact it is having are naturally causing a lot of fear, uncertainty and anxiety across the world.This situation is particularly stressful because,we cann’'t predict how things will develop.There is always an uncertainty of our circumstances.The purpose of this project is to evalute various characteristic from New York City COVID-19 dataset to identify the key findings of the data.
Roles
Square: Rita; Triangle: Julia; Circle: Sharmin (Supervised Machine Learning)
Google Slides
Actual Link: https://docs.google.com/presentation/d/1AikBbD5WhO2oSrPKW-P_DM_hEYEP0Ak2Z516GCudWLo/edit#slide=id.p
Reason why they selected their topic
We selected the topic of COVID-19, because we are currently in a situtation where there are still relatively high numbers of people with COVID-19.
Description of their source of data
Our dataset comes from NYC open data repository, Data Provided by Department of Health and Mental Hygiene (DOHMH).The dataset shows outcomes (confirmed cases, hospitalizations, and deaths) for cohorts defined by each date of specimen collection (specimen_date). For example, if a NYC resident tested positive for SARS-CoV-2 and was subsequently hospitalized, both events would show under the same specimen_date, indicating the date of specimen collection for the positive test and not the date of the hospitalization.
The data consists of covid-testing specimens, the extracted date of the specimen results, the number of people tested, the number of people who were tested positive for COVID-19, the number of COVID-19 people who were hospitalized, as well as the number of people who passed away in the hospital due to COVID-19.
Questions they hope to answer with the data
* Does the number of COVID-19 patients hospitalized correlate with the average percentage of COVID-19
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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