将 BlankerL 提供的2019新型冠状病毒疫情时间序列数据仓库进行可视化。目前为自用，可提供市级的确诊数、治愈数、死亡数时程线，（各大网站只提供全国确诊数的时程线）。 目前提供中文、英文两种输出。
注意本项目使用的是丁香园（DXY）的国内数据。
若对全球趋势感兴趣，可参见另一个项目（也是本项目的一个重写）：https://github.com/lyupin/plot-timehistory-open-covid-19
也可参考下面所附的其它英文链接。
Visualize the time-history of important daily counts in COVID-19 in China. The data is stored in another author's repository: https://github.com/BlankerL/DXY-COVID-19-Data , which is gathered by the website Ding Xiang Yuan focusing on epidemic situation in China.
This visualization script is not for COVID-19 worldwide.
If you are looking for data and visualization outside of China, maybe you can try these:
- My another repository for worldwide COVID-19 timehistory: https://github.com/lyupin/plot-timehistory-open-covid-19
- GIS for worldwide situation provide by JHU: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
- North America visualization provided by "一亩三分地": https://coronavirus.1point3acres.com/
- Worldwide data and visualization compiled by Chinese media ThePaper.cn: https://github.com/839-studio/novel-coronavirus-updates
However, the features are quite limited by now as it is for my personal use. (I live in the epicenter of the pandemic, Wuhan City, Hubei Province. I care about the trend.)
The daily increment will be calculated and plotted so that we are aware of the trend.
The data is provided by BlankerL at his repository DXY-COVID-19-Data.
打开VisualizeDXYArea.py，填入语种、感兴趣的省名、市名、数据文件的路径，保存后，运行
Open VisualizeDXYArea.py, fill the language, the names of interested cities or provinces, save and run:
python VisualizeDXYArea.py
将生成png格式的时程线图片。
Time-histories will be saved as figures in format of png.
除标准python库外，需额外安装的库有：
Besides the standard python 3 library, you need these libs installed:
matplotlib pandas