中国COVID-19疫情时空数据集
中国COVID-19疫情时空数据集，提供城市/县级每日新增感染、累计感染等六项关键数据，共368条记录，覆盖2020年1月20日至2月29日，错误率仅0.04%，用于区域传播动态研究。
基本信息
资源简介
该数据集由南洋理工大学物理与数学科学学院创建，提供中国各城市/县级的COVID-19疫情每日统计数据，包括每日新增感染、累计感染、每日新增康复、累计康复、每日新增死亡和累计死亡共六项关键指标，共计368条记录，覆盖2020年1月20日至2月29日。数据源自中国官方网站，经严格验证，错误率仅0.04%，适用于区域级COVID-19传播动态研究，有助于政策制定者制定干预和缓解策略。
下载信息
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使用方式
数据集获取
git clone https://github.com/cheongsa/Coronavirus-COVID-19-statistics-in-China.git
curl -L -o repo.zip https://github.com/cheongsa/Coronavirus-COVID-19-statistics-in-China/archive/refs/heads/master.zip
unzip repo.zip
源站 README 摘录（使用方式）
Coronavirus (COVID-19) statistics in China
A data set on COVID-19 pandemic in China, which covers daily statistics of confirmed cases (new and cumulative), recoveries (new and cumulative) and deaths (new and cumulative) at city level.
All data are extracted from Chinese government reports.
We have finished the data clean, so enjoy the dataset and have fun.
If you find this dataset useful in your research please consider citing:
@article{liu2020coronavirus,
title={Coronavirus disease 2019 (COVID-19) outbreak in China, spatial temporal dataset},
author={Wenyuan Liu and Peter Tsung-Wen Yen and Siew Ann Cheong},
year={2020},
eprint={2003.11716},
archivePrefix={arXiv},
primaryClass={q-bio.PE}
}
File format
Each file contains 393 lines and 44 columns: the first row is the header, the name for each column, while other rows are the data for all cities/counties. For each row, the first four columns are names for city/county: the first cloumns is the name of city/county in English, the second column is the name of the provincial-level region this city/county belongs to in English, the third column is the name of city/county in Chinese, and the fourth column is the name of the provincial-level region this city/county belongs to in Chinese. The remaining columns are dates ranging from 20 January 2020 to Febraruy 29 2020 (in YYYY-
MM-DD format). For example, in China_accumulated_infections.csv, for row 1, column 1 is “Beijing Municipality”, whereas, column 20 (2020-02-04) is 253. This tells us that there are 253 confirmed cases reported in Beijing up till 24:00 4 Febraruy 2020.
Gallery
import pandas as pd
import matplotlib.pyplot as plt
new_infectionevent-blocked= pd.read_csv("China_daily_new_infections.csv")
total_infectionevent-blocked= pd.read_csv("China_accumulated_infections.csv")
Wenzhou = total_infections[total_infections[''Prefectural level or Country level''] == "Wenzhou"]
dates = Wenzhou.columns[4:].tolist()
numbers = Wenzhou.iloc[0].tolist()[4:]
fig, ax = plt.subplots()
ax.bar(dates, numbers)
plt.xticks(dates, dates, rotation=''vertical'')
plt.title("Wenzhou")
province_data = new_infections.groupby(''Provincial-level regions'').sum().reset_index()
dates = province_data.columns[1:].tolist()
Anhui = province_data[province_data[''Provincial-level regions''] == "Anhui"]
Guangdonevent-blocked= province_data[province_da
## 数据加载示例（表格/文本类）
```python
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/cheongsa/Coronavirus-COVID-19-statistics-in-China
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