#
2019-ncov
Here are 164 public repositories matching this topic...
Open
从4-1开始加入了无症状感染者的数据
2
Tigsi
opened
Apr 2, 2020
Open
丁香医生的疑似确诊已改变
1
2019新型冠状病毒疫情时间序列数据仓库 | COVID-19/2019-nCoV Infection Time Series Data Warehouse
-
Updated
May 6, 2020 - Python
awesome
corona
awesome-list
epidemiology
2019-ncov
2019ncov
coronavirus
coronavirus-info
covid-19
covid19
sars-cov-2
covid19-data
awesome-corona
awesome-coronavirus
2019-ncov-data
-
Updated
May 6, 2020 - JavaScript
JSON time-series of coronavirus cases (confirmed, deaths and recovered) per country - updated daily
-
Updated
May 6, 2020 - JavaScript
1
Data on COVID-19 confirmed cases, deaths, and tests • All countries • Updated daily by Our World in Data
-
Updated
May 6, 2020 - Python
Covidify - corona virus report and dataset generator for python 📈
virus
china
trend
pandemic
deaths
wuhan
2019-ncov
ncov
2019ncov
coronavirus
2020ncov
coronavirus-real-time
wuhan-virus
recoveries
aggregated-sums
coronavirus-analysis
confirmed-cases
jhu-csse
covid-19
covid-virus
covid
covidify
-
Updated
May 1, 2020 - Jupyter Notebook
query stats of infected coronavirus cases
-
Updated
Apr 10, 2020 - R
Open
Deploy this in macOS
1
estebaniglesias
commented
Apr 7, 2020
Hello! Thank you very much for this tool.
I have been trying to deploy this webapp in my macOS, and I have got a lot of issues. Hopefully, with a help of a friend, some coffe and a good amount of hours I ended up with these instructions:
- You'll need to have "tac" command. Is included in linux, but not nativelly, at least in my version of macOS
brew update
brew install coreutils
bre
hugetiny
opened
Feb 24, 2020
Informationssammlung zum Thema CoVid-19
-
Updated
May 4, 2020
chart
charts
dashboard
2019-ncov
coronavirus
coronavirus-tracking
coronavirus-real-time
ncov-2019
covid-19
covid19
-
Updated
Apr 15, 2020 - JavaScript
-
Updated
May 6, 2020 - R
👩🏻⚕️Covid-19 estimation and forecast using statistical model; 新型冠状病毒武汉肺炎统计模型预测
-
Updated
Feb 23, 2020 - Jupyter Notebook
A global collection of Open Source projects during COVID-19
open-source
world
japan
china
korea
iran
italy
mainland-china
wuhan
2019-ncov
ncov
coronavirus
covid-19
sars-cov-2
open-source-wuhan
open-source-covid
awesome-coronavirus
awesome-covid-19
-
Updated
May 6, 2020 - Python
Tracking Coronavirus Growth
-
Updated
Apr 7, 2020 - Jupyter Notebook
Use Google Maps Timeline data to compare with COVID-19 patient history location.
-
Updated
May 1, 2020 - JavaScript
Ongoing analysis of COVID-19 using Galaxy, BioConda and public research infrastructures
-
Updated
May 6, 2020 - Jupyter Notebook
中国社会与政治事件时间线展示和新闻事件提交网站
society
ideology
human-rights
totalitarians
2019-ncov
wuhan-pneumonia
wuhan-coronavirus-outbreak
chinese-communist-party
-
Updated
May 6, 2020 - HTML
Modelling of the nCoV-2019 outbreak in Wuhan, China, by Jon Read, Jess Bridgen, and Chris Jewell at Lancaster University.
-
Updated
Feb 17, 2020 - R
COVID-19 datasets are constructed entirely from primary (government and public agency) sources
-
Updated
May 6, 2020
Systematic dataset of Covid-19 policy, from Oxford University
-
Updated
May 6, 2020
Coronavirus COVID-19 (2019-nCoV) Epidemic Datasets
-
Updated
May 6, 2020 - R
Python graph traversal algorithm implementation including BFS, DFS, Topological Sort, Dijkstra, Prim, Borůvka, Kruskal, A*, Bellman Ford, Bron Kerbosch
discrete-mathematics
graph-theory
agent-based-modeling
differential-equations
network-analysis
maximal-cliques
bron-kerbosch-algorithm
random-graph
complex-network
agent-based-simulation
sir-model
dynamic-network
dynamic-system
epidemic-model
compartmental-model
k-core
2019-ncov
coronavirus
covid-19
sars-cov-2
-
Updated
May 3, 2020 - Jupyter Notebook
COVID-19 interactive dashboard for the whole world
-
Updated
May 6, 2020 - JavaScript
Improve this page
Add a description, image, and links to the 2019-ncov topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the 2019-ncov topic, visit your repo's landing page and select "manage topics."
We will update the time series tables in the following days, aiming to provide a cleaner and more organized dataset consistent with our new/current naming convention. We will also be reporting a new variable (i.e, testing), as well as data at the county level for the US. All files will continue to be updated daily around 11:59PM UTC.
The followiing specific changes will be made: