# COVID-19 Insights for India
This notebook provides a catalog of open datasets for deriving insights related to COVID-19 and helping open source and open data community to collaborate in fighting this global threat. The notebook provides (a) reusable API to speed up open data analytics related to COVID-19, customized for India however can be adopted for other countries, (b) sample usage of the API, (c) documentation of insights, and (d) catalog of open datasets referenced.
The notebook is created by aggregating content from hundreds of global contributors, whome we have tried our best to acknowledge, if you note any missed ones, please inform us by creating an issue on this Github repository. The code, links, and datasets are provided on AS-IS basis under open source. This is the work of the individual author and contributors to this repository with no endorsements from any organizations including their own.
```python
%matplotlib inline
import covid as cv
```
```python
df = cv.get_today_stats(force=True)
```
Creating stats for today...
Stats file for today saved: 2020-03-24-covid-india-stats.csv
```python
cv.summary_stats(df)
```
| Latest |
| Indian |
476 |
| Foreign |
43 |
| Discharged |
40 |
| Death |
10 |
| Confirmed |
519 |
| Active |
469 |
```python
cv.display_stats(df)
```
| State | Indian | Foreign | Discharged | Death | Confirmed | Active |
| 8 |
Kerala |
87 |
8 |
4 |
0 |
95 |
91 |
| 10 |
Maharashtra |
86 |
3 |
0 |
2 |
89 |
87 |
| 17 |
Telengana |
25 |
10 |
1 |
0 |
35 |
34 |
| 7 |
Karnataka |
37 |
0 |
3 |
1 |
37 |
33 |
| 4 |
Gujarat |
32 |
1 |
0 |
1 |
33 |
32 |
| 15 |
Rajasthan |
30 |
2 |
3 |
0 |
32 |
29 |
| 14 |
Punjab |
29 |
0 |
0 |
1 |
29 |
28 |
| 21 |
Uttar Pradesh |
32 |
1 |
11 |
0 |
33 |
22 |
| 3 |
Delhi |
29 |
1 |
6 |
2 |
30 |
22 |
| 5 |
Haryana |
14 |
14 |
11 |
0 |
28 |
17 |
| 16 |
Tamil Nadu |
13 |
2 |
1 |
0 |
15 |
14 |
| 20 |
Ladakh |
13 |
0 |
0 |
0 |
13 |
13 |
| 0 |
Andhra Pradesh |
8 |
0 |
0 |
0 |
8 |
8 |
| 23 |
West Bengal |
9 |
0 |
0 |
1 |
9 |
8 |
| 9 |
Madhya Pradesh |
7 |
0 |
0 |
0 |
7 |
7 |
| 18 |
Chandigarh |
7 |
0 |
0 |
0 |
7 |
7 |
| 19 |
Jammu and Kashmir |
4 |
0 |
0 |
0 |
4 |
4 |
| 22 |
Uttarakhand |
3 |
1 |
0 |
0 |
4 |
4 |
| 1 |
Bihar |
3 |
0 |
0 |
1 |
3 |
2 |
| 6 |
Himachal Pradesh |
3 |
0 |
0 |
1 |
3 |
2 |
| 12 |
Odisha |
2 |
0 |
0 |
0 |
2 |
2 |
| 13 |
Puducherry |
1 |
0 |
0 |
0 |
1 |
1 |
| 11 |
Manipur |
1 |
0 |
0 |
0 |
1 |
1 |
| 2 |
Chhattisgarh |
1 |
0 |
0 |
0 |
1 |
1 |
```python
cv.linear_regression(df)
```
### COVID-19 Open Datasets, Dashboards, and Apps
#### India Stats
1. [Ministry of Health and Family Welfare - MOHFW](https://www.mohfw.gov.in/) publishes COVID India stats. This notebook pulls the stats from HTML table on site.
2. [India Affected People Dataset](http://portal.covid19india.org/) by covid19india.org
3. [Patient Travel History](https://api.covid19india.org/travel_history.json) by covid19india.org
#### India Dashboards
1. Kiprosh [covidout.in dashboard](https://covidout.in/) provides MOHFW stats, daily and cummulative trends.
#### India Apps
1. [COVID-19 India Cluster Graph Visualization](https://cluster.covid19india.org/) by covid19india.org
#### India Hospitals, Testing Labs
1. [ICMR](https://icmr.nic.in/what-s-new) List of Government [Laboratories](https://icmr.nic.in/sites/default/files/upload_documents/Govt_Lab_COVID_19_Testing_V2.pdf) for COVID-19 Testing
2. Statewise Hospital Beds from [PIB](https://pib.gov.in/PressReleasePage.aspx?PRID=1539877) extracted to [CSV dataset](https://www.kaggle.com/sudalairajkumar/covid19-in-india#HospitalBedsIndia.csv) on Kaggle.
#### Census, Demographics
1. India rural, urban population and area by states on [Wikipedia](https://en.wikipedia.org/wiki/List_of_states_and_union_territories_of_India_by_population) extracted to [CSV dataset](https://www.kaggle.com/sudalairajkumar/covid19-in-india#population_india_census2011.csv) on Kaggle.
2. [World Bank Indicators](https://data.humdata.org/dataset/world-bank-indicators-of-interest-to-the-covid-19-outbreak) of Interest to the COVID-19 Outbreak.
#### Global Stats
1. [Geographic distribution of COVID-19 cases worldwide](https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide) from European Centre for Disease Prevention and Control available as daily [Excel dataset](https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide-2020-03-22.xlsx) (2020-03-22). Replace yyyy-mm-dd suffix on file to get historical/current data.
2. Johns Hopkins University [Global Dashboard](https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6) and GitHub [datasets](https://github.com/CSSEGISandData/COVID-19).
3. Situational Awareness Dashboard from [World Health Organization](https://experience.arcgis.com/experience/685d0ace521648f8a5beeeee1b9125cd).
#### Research
1. COVID-19 [Open Research Dataset](https://pages.semanticscholar.org/coronavirus-research) (CORD-19) from Allen Institute for AI. Contains over 44,000 scholarly articles, including over 29,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community.
2. NCBI [SARS-CoV-2 Genetic Sequences](https://www.ncbi.nlm.nih.gov/genbank/sars-cov-2-seqs/)
3. Nextstrain [Genomic epidemiology of novel coronavirus](https://nextstrain.org/ncov)
4. GISAID App for [Genomic epidemiology of hCoV-19](https://www.gisaid.org/epiflu-applications/next-hcov-19-app/)
#### News Analysis
1. ACAPS COVID-19: [Government Measures Dataset](https://data.humdata.org/dataset/acaps-covid19-government-measures-dataset)
#### Notebooks
1. Notebook from Parul Pandey on [Tracking India's Coronavirus Spread](https://www.kaggle.com/parulpandey/tracking-india-s-coronavirus-spread-wip/notebook) compares trends across India, Italy, Korea.
2. [COVID-19 Literature Clustering](https://www.kaggle.com/maksimeren/covid-19-literature-clustering) visualizes CORD-19 dataset of over 44,000 scholarly articles.
3. [Coronavirus (COVID-19) Visualization & Prediction](https://www.kaggle.com/therealcyberlord/coronavirus-covid-19-visualization-prediction) does timeseries predictive analysis of virus spread based on Johns Hopkins dataset.
#### Meta Dataset Sources
1. [Registry of Open Data on AWS](https://registry.opendata.aws/)
2. [MyGov COVID-19 Solution Challenge / Resources](https://innovate.mygov.in/covid19/#tab6)
3. [Covidout Data Sources](https://covidout.in/sources)
4. [Kaggle COVID datasets](https://www.kaggle.com/search?q=covid+coronavirus+in%3Adatasets)
5. [HDX Datasets on COVID-19 Outbreak](https://data.humdata.org/event/covid-19)
6. [api.rootnet.in](https://api.rootnet.in/) multiple official and unofficial India specific datasets as JSON files