Saravanan666/pypi-org huggingface dataset:
Package: covid19-us
covid19-usOverviewThis package aims to provide a streamlined way to download historical covid data from the United States. We support the historical data sliced by state, county and zip code through three easy-to-use APIs:download_by_state,download_by_countyanddownload_by_zip_code.Note that for most input variables, we support either a string or a list. For example, ‘zip_code_list’ can be either38120or[‘38120’, ‘02472’]. If it’s the latter case, two result sets will be concatenated and returned as a pandas dataframe.Free software: MIT licenseFeaturesDownload data by state in the United Statesdownload_by_state()is a function to download daily data from a given state. An example is illustrated as follows. Note that the following functions typically can accept both list type or string type. In other words,[‘SC’]andSCcan be both understood as South Carolina correctly.fromcovid19_usimportdownload_by_statesc_three_days=download_by_state(state='SC',dates=['2020-12-31','2021-01-01','2021-01-02'])sc_three_days[['state','date','cases','deaths']]statedatecasesdeaths0SC2021-01-02 00:00:005211891SC2021-01-01 00:00:00002SC2020-12-31 00:00:00403247Download data by county in the United Statesdownload_by_county()is a function to download daily data from a given county or counties. An example is illustrated as follows. We support both county name and county FIPS, a unique identifier.fromcovid19_usimportdownload_by_countyfrompandasimportdate_rangerichland_2020=download_by_county(states='SC',counties='Richland',dates=date_range('2021-02-10','2021-02-15'))countydatedeathscasesdeaths_cumulativecases_cumulative888738Richland2021-02-10 00:00:00517345737804888739Richland2021-02-11 00:00:00320846038012888740Richland2021-02-12 00:00:00123946138251888741Richland2021-02-13 00:00:00223946338490888742Richland2021-02-14 00:00:00331246638802888743Richland2021-02-15 00:00:00616447238966download data by zip code in the united statesdownload_by_zip_code()is function to download daily data from a given zip code. Again, this is not exactly count by zip code, but the county total where the zip code resides in.fromcovid19_usimportdownload_by_zip_codetn_new_year=download_by_zip_code(zip_code_list=['38120'],dates=['2021-01-01','2021-01-02','2021-01-03'])countystatefipsdatedeaths_cumulativecases_cumulativedeathscases953003ShelbyTN471572021-01-01 00:00:00903678000602953004ShelbyTN471572021-01-02 00:00:0091469798111998953005ShelbyTN471572021-01-03 00:00:009257014211344CreditsThe data source is fromthe New York Times. The author would also like to express his gratitude for the agency’s effort to achieve outstanding journalism.History0.1.0 (2021-03-22)First release on PyPI.
Package: covid19-utpl
Proyecto Final, Segundo Bimestre - PYTHON BÁSICOVencimiento: Miércoles, 27 de julioCalificación: .../10 (Auto califique su trabajo)Objetivos de aprendizajeAplicar nuevas habilidades a un problema del mundo realSintetizar las técnicas aprendidasHerramientasgitgithubpythonpoetrypandasnumpyclickmatplotlibOrganización de carpetasArchivos generados automáticamente por poetrycovid19_utpl
├── pyproject.toml              
├── README.md                   # Documentación del proyecto    
├── covid_19_utpl
│    └── __init__.py
│    └── main.py 
│    └── data
│       └── vacunometro_cantones.csv
│    └── img
│        └── Vacunados_Canton.png
│    └── src
│       └── __init__.py
│       └── conexion.py
│       └── grafica.py
│       └── listados.py
│       └── vacunados.pyDescripciónCovid19_UTPL es una aplicacion desarrollada en Python que procesa informacion de la vacunacion del Ecuador, presentando informacion
como seleccione el usuario ya sea por regiones, provincias o cantones, grafica cuantos han sido vacunados y las fechas que se ha desarrollado
de las diversas dosis de vacunacion.Versiones y evoluciones del productoVersión 1.0.1 Julio 2022Creacion de menusObtencion de datosCreacion de funcionesVersión 1.0.2 Junio 2022Guardado de graficasPublicacion PypiProyecto Final
Package: covidactnow
Covid Act Now Database WrapperThis package is an extremely bare-bones wrapper around Covid Act Now's database of COVID-19 related information. View the PyPi projecthere, and the original post pagehere.Usage is simple. Install the package withpip install covidactnow.Instantiate a user object with your API key as an argument. You can easily generate an API keyhere.importcovidactnowapi=covidactnow.User(api_key='yourapikey')washingtonInfectionRate=api.infRate('WA')massachussettsVaxRate=api.vaxRate('MA')print(f"{washingtonInfectionRate= }")print(f"{massachussettsVaxRate= }")This will result (with different data, of course):washingtonInfectionRate = 1.16
massachussettsVaxRate = 76.3To view the docstring (explainer) of a particular function, usecovidactnow.User.infRate.__doc__whereinfRatecan be repalced with any other function. For example, runningprint(covidactnow.User.freeBedPercentage.__doc__)will return:Get's the percentage of free hospital beds by state.Depending on your IDE, hovering over a function in the editor will show the function's docstring (works in VS Code).importcovidactnowif__name__=="__main__":print(covidactnow.User.infRate.__doc__)print(covidactnow.User.freeBedPercentage.__doc__)""" Result:>>> Gets today's COVID infection rate by state.>>> Get's the percentage of free hospital beds by state."""----Formoreinformationonhowthewrapperworks,particularlyhowitwasredesignedtobepackage-friendly,readthe"Updated for Distribution"sectionofthis[page](https://covidinfo.preritdas.com).Notethatthisversionhasbeenupdatedtogetdatafromwithina`User`classallowingindividualAPIkeystobeused(asopposedtodefiningastateasanobjectanddefiningstatisticsasobjectattributes).
Package: covidata
CovidataEasily access NASA, ESA and JAXA dataAboutYou can use this API to access and see statistics about NASA, JAXA and ESA datasets. Check the available datasets and how to use them bellow.Available DatasetsESAmortality and natality
coronavirus cases worldwideJAXAgreenhouse gases concentrationNASAlandslides
atmospherical dataMain FunctionsConstructorsInitialize an object with the required dataDescribeGenerete statistics about all the features in the dataset, such as mean, standard deviation and quartiles.Examplesfromcovidata.nasaimportLandslidesLS=Landslides(subset=100,verbose=True)print(LS.summarize())print(LS.head())
Package: covidbeta
covidbetaThe goal of this project is to visualize expected number of new infections and new deaths by country due to Covid-19.Using a OWID dataset, covidbeta can visualize Expected number of new infections and new deaths by country due to Covid-19.The OWID dataset is downloadable from:https://github.com/owid/covid-19-data/tree/master/public/data/vaccinationsHow to install covidbeta on Linux, MacOS, or WSL on Windows$ pip install covidbetaHow to run covidbeta$ covidbeta
Package: covid-big-bappenas
Covid-Big-Bappenas PackageA helper pip package for Covid BIG BAPPENAS ProjectAssumptions:Assuming python is installed on your system.Installation sets up commandSituation before installation::$ covid_big_bappenas
bash: covid_big_bappenas: command not foundInstallation right from the source tree (or via pip from PyPI)::$ python setup.py install

$ pip install covid_big_bappenasNow, thecovid_big_bappenascommand is available::$ covid_big_bappenas --helpWelcome to Covid-Big-Bappenas Package!Author: Muhammad Hasannudin Yusa
Office: Pusat PPIG - Badan Informasi Geospasial
Email:muhammad.hasannudin@big.go.idUsage: main.py [OPTIONS] TASKOptions:
--key TEXT  The key to login.
--help      Show this message and exit.$ covid_big_bappenas --key d0osm19di1o************** indikator1Welcome to Covid-Big-Bappenas Package!Author: Muhammad Hasannudin Yusa
Office: Pusat PPIG - Badan Informasi Geospasial
Email:muhammad.hasannudin@big.go.idTask: indikator1
Harvester is initiated!
Try to connect to BLC:https://data.covid19.go.idHarvest data for indikator1
Connected!
Get list all regencies and municipalities
Done!
Harvesting is started
1, ACEH - ACEH BARAT
2, ACEH - ACEH BARAT DAYA
3, ACEH - ACEH BESAR
...
512, SUMATERA UTARA - TAPANULI TENGAH
513, SUMATERA UTARA - TAPANULI UTARA
514, SUMATERA UTARA - TOBA SAMOSIR
Harvesting is finished
Data is saved successfully. The file name is 20200714-123250_indikator1_kabkot.csv$ covid_big_bappenas indikator1
Welcome to Covid-Big-Bappenas Package!===============================================
Author: Muhammad Hasannudin Yusa
Office: Pusat PPIG - Badan Informasi Geospasial
Email:muhammad.hasannudin@big.go.idYour key: d0osm19di1o**************
Task: indikator1
Harvester is initiated!
Try to connect to BLC:https://data.covid19.go.idHarvest data for indikator1
Connected!
Get list all regencies and municipalities
Done!
Harvesting is started
1, ACEH - ACEH BARAT
2, ACEH - ACEH BARAT DAYA
3, ACEH - ACEH BESAR
...
512, SUMATERA UTARA - TAPANULI TENGAH
513, SUMATERA UTARA - TAPANULI UTARA
514, SUMATERA UTARA - TOBA SAMOSIR
Harvesting is finished
Data is saved successfully. The file name is 20200714-123250_indikator1_kabkot.csv$ covid_big_bappenas indikator3
Welcome to Covid-Big-Bappenas Package!===============================================
Author: Muhammad Hasannudin Yusa
Office: Pusat PPIG - Badan Informasi Geospasial
Email:muhammad.hasannudin@big.go.idYour key: d0osm19di1o**************
Task: indikator3
Harvester is initiated!
Try to connect to BLC:https://data.covid19.go.idHarvest data for indikator3
Connected!
Get list all provinces
Done!
Harvesting is started
1, PAPUA BARAT
2, BANTEN
3, KALIMANTAN SELATAN
...
32, SULAWESI UTARA
33, SULAWESI TENGAH
34, PAPUA
Harvesting is finished
Data is saved successfully. The file name is 20200714-123107_indikator3_prov.csv
Package: covidbr
CovidBrLibrary for data mining about covid-19 in brazilian cities 📈📊📚Installation$pipinstallcovidbr-UExamplesGet data from citiesimportcovidbrascbcb.show_console(True)place='Juazeiro BA'data_pet=cb.city(place)getting the light data and working with itdataset=data_city.dadosdadoscasosmortosmortes_diariascasos_diariospopulation23/mar/2020100121816224/mar/2020200121816225/mar/2020200021816226/mar/2020200021816227/mar/20202000218162..................26/dez/2021187524170021816227/dez/2021187524170021816228/dez/2021187524170021816229/dez/2021187524170021816230/dez/20211875241700218162[648rowsx5columns]getting the data of death's:mortos=dataset['mortos']mortos23/mar/2020024/mar/2020025/mar/2020026/mar/2020027/mar/20200...26/dez/202141727/dez/202141728/dez/202141729/dez/202141730/dez/2021417Name:mortos,Length:648,dtype:int64getting the data of case's:casos=dataset['casos']23/mar/2020124/mar/2020225/mar/2020226/mar/2020227/mar/20202...26/dez/20211875227/dez/20211875228/dez/20211875229/dez/20211875230/dez/202118752Name:casos,Length:648,dtype:int64getting the mortality percent:perc_m=(mortos/casos)*100perc_m23/mar/20200.00000024/mar/20200.00000025/mar/20200.00000026/mar/20200.00000027/mar/20200.000000...26/dez/20212.22376327/dez/20212.22376328/dez/20212.22376329/dez/20212.22376330/dez/20212.223763
Length:648,dtype:float64
Package: covidcasev
covidcasevThe goal of this project is to visualize the number of infected people by country due to Covid-19.Using a OWID dataset, covidcasev can visualize the number of infected people by country due to Covid-19.The OWID dataset is downloadable from:https://github.com/owid/covid-19-data/tree/master/public/data/vaccinationsHow to install covidcasev on Linux, MacOS, or WSL on Windows$ pip install covidcasevHow to run covidcasev$ covidcasev countryex. $ covidcasev Japan
Package: covidcast
COVIDcast API clientProvides Python access to theCOVIDcast
APIpublished
by theDelphi groupatCarnegie Mellon
University. This API provides daily access to a range of
COVID-related signals Delphi collects from a variety of sources, including
cases, deaths, symptom surveys, healthcare data, and other information. This
package also provides convenient tools for mapping and analyzing the API's data.For installation instructions, documentation, and examples, consult thepackage
documentation.
Package: covid-cli
Get the latest COVID-19 information via the command line.Installationpip install covid-cliUsageusage: covid [-h] [-all] [-country COUNTRY] [-totals] [-csv] [-us]
             [-sort-by [{Country,Active,Cases,Deaths,Recovered,Death Rate}]]

optional arguments:
  -h, --help            show this help message and exit
  -all, -a              Get all countries totals
  -country COUNTRY, -c COUNTRY
                        Get a specific country's totals.
  -totals, -t           Get global stats: cases, deaths, recovered, time last
                        updated, and active cases
  -csv                  Set this flag to output to CSV.
  -us, -u               Get United States data.
  -sort-by [{Country,Active,Cases,Deaths,Recovered,Death Rate}], -s [{Country,Active,Cases,Deaths,Recovered,Death Rate}]
                        Sort data by column.Demo
Package: covid-dashboard-jadam
## README
### Introduction
This project aims to provide a simple, personalisable dashboard for Covid data and news. Users can schedule updates to the data and news stories on top of those that already automatically occur. They can also customise what area they receive Covid data for to, as well as what sort of news they receive.
___
#### Prerequisites
Designed for Python 3.9
Sched and Flask modules
Public Health England Covid data API module
News Api module andkey- can be gotten for free fromhttps://newsapi.org/register___
### Installationpip install schedule
pip install Flask
pip install uk-covid19
pip install NewsApi
___
### Getting started
Firstly you must open the config file and put your API key in for /key/. Next run main.py, this will start the server. The dashboard can now be accessed athttp://127.0.0.1:5000/index.
In order to change where Covid data is shown for, or what keywords are used to filter news stories, change the relevant lines in the config file
___
### Developer documentation___
Author - James Adam
Package: covid-data-api
COVID-19 DATA APIThis package makesCOVID-19data available through python API. All the data are directy taken from theCSSEGISandData-covi19with the below mentioned data sources. There are several methods to extract the statistics and counts for the coutry or province.Installation:Also available in pypi:covid-data-apiFrom GitHub:Clone this repo.pip install -r requirements.txtpython setup.py installHow to user:Initialising the instance/api:from covid.api import CovId19Data

api = CovId19Data(force=False)If force = True, every time object is instantiated new data is downloaded. Otherwise data will be refreshed after 24 hrs.Method 1: Get stats:Get the latest total stats for all confirmed, deaths and recovered till the latest date available.res = api.get_stats()Method 2: Get records for all the countries:res = api.get_all_records_by_country()Method 3: Get records for all the state/Province:res = api.get_all_records_by_provinces()Method 4: Filter by Country:To find all the countries availabe, plese use show_all_available_countries api.res = api.filter_by_country("ireland")Method 5: Filter by Province/State:To find all the countries availabe, plese use show_all_available_regions api.res = api.filter_by_province("British Columbia")Method 6: Show all available Countries:res = api.show_available_countries()Method 7: Show all valiable Province/State:res = api.show_available_regions()Method 8: Get history data for a given Country:res = api.get_history_by_country("ireland")Shows all the country metrics confirmed, recovered and deaths for the dates till the latest date.Method 9: Get history data for a given State/Province:res = api.get_history_by_province("British Columbia")Shows all the state/province metrics confirmed, recovered and deaths for the dates till the latest date.Data Sources:All used data sourcesCSSEGISandData-covi19.Support and Maintenance:Please raise an issues with issues of this git repo. This is not actively supported, however anyone with the interest can solve the raised issues.Copying and LicenseTerms and conditions of the data provider:CSSEGISandData-covi19Terms and Condition of this repo:License:MITAuthors:gtkChopvipin-techsee alsocontributorsChangeLog:1.1, 1.2, 1.3 - Initial Versions1.4 - Change in recovered cases in source CoViD data repository.
Package: covid-data-by-zip-code
covid_data_by_zip_codethis package provides a streamlined way to download covid data by stateFree software: MIT licenseDocumentation:https://covid-data-by-zip-code.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-03-22)First release on PyPI.
Package: covidify
covidifyFeatures•How To Use•Install•Visualizations•Data Source•Credits•To-Do ListFeaturesCovidify downloads the latestcovid-19data for confirmed cases, deaths and recoveries.Creates a time series datasetCreates a daily stats datasetForecast global and country confirmed casesGenerate visualizationsFilter by countryList all countries affectedShows number of people currently infectedGenerates an excel report including all of the aboveInstallpip install covidifyHow to use$covidifyUsage:covidify[OPTIONS] COMMAND [ARGS]...☣COVIDIFY☣-usethemostup-to-datedatatogeneratereportsofconfirmedcases,fatalitiesandrecoveries.Options:--helpShowthismessageandexit.Commands:listListallthecountriesthathaveconfirmedcases.runGeneratereportsforglobalcasesorrefinebycountry.$covidifyrun--helpUsage:covidifyrun[OPTIONS]Options:--outputTEXTFoldertooutputdataandreports[Default:/Users/award40/Desktop/covidify-output/]--sourceTEXTTherearetwodatasourcestochoosefrom,JohnsHopkinsgithubrepoorwikipedia--optionsareJHUorwikirespectively[Default:JHU]--countryTEXTFilterreportsbyacountry--topTEXTTopNinfectedcountriesforlogplot.[Default:10]--forecastTEXTNumberofdaystoforecastcumulativecasesinthefuture.[Default:15]--helpShowthismessageandexit.Example Commands:# List all countries affectedcovidifylist--countries# Will default to desktop folder for output and github for datasourcecovidifyrun# Specify output folder and sourcecovidifyrun--output=<PATHTODESIREDOUTPUTFOLDER># Filter reports by countrycovidifyrun--country="South Korea"# Show top 20 infected countries on a logarithmic scalecovidifyrun--top=20# Forecast cumulative cases in America for 14 days into the futurecovidifyrun--country=America--forecast=14VisualizationsAn excel spreadsheet is generated with a number of visualizations and statistics.Logarithmic PlotThis plot shows the topNinfected countries on a logarithmic scale.ForecastingAn ARIMA model is trained and used to forecast the cumulative cases forNnumber of days
into the future (DISCLAIMER: the forecast is a ballpark figure, and should not be taken as gospel)Accumulative TrendThis is an accumulative sum trendline for all the confirmed cases, deaths and recoveries.Daily TrendlineThis is a daily sum trendline for all the confirmed cases, deaths and recoveries.Stacked Daily Confirmed CasesThis stacked bar chart shows a daily sum of people who are already confirmed (red) and the people who have been confirmed on that date (blue)Daily Confirmed CasesA count for new cases on a given date, does not take past confirmations into account.Daily DeathsA count for deaths on a given date, does not take past deaths into account.Daily RecoveriesA count for new recoveries on a given date, does not take past recoveries into account.Currently InfectedA count for all the people who are currently infected for a given date.CreditsWritten by me (Aaron Ward  -https://www.linkedin.com/in/aaronjward/)A special thank you to theJHU CSSEteam for maintaining the dataAlso a special thank you to @ajaymaity for bug fixes 🎉
Package: covidillness
DescriptionThis can be seen in the graph of the number of ICU patients and deaths due to Covid-19.The data can be found at the following URL：https://covid.ourworldindata.org/data/owid-covid-data.csvHow to install covidillnessWrite the following program in the terminal on your computer.$ pip install covidillnessHow to run covidillness$ covidillness Japan FranceThe vertical axis of the above graph represents the number of deaths due to Covid-19.The lower graph shows the number of ICU patients.In both Japan and France, the number of ICU patients fluctuates regardless of the number of Covid-19 deaths.Written by Izuru Inose-At the Takefuji Lab-
Package: covidimpact
How to install covidimpact$ pip install covidimpactHow to run covidimpact$ covidimpactEnter the number of the menu displayed.Disease of HeartThe vertical axis is the number of deaths from the selected cause of death.
The number of deaths due to Disease of Heart has increased more than any other.Drug OverdoseThe number of deaths due to Drug Overdose has increased dramatically since 2019, the Covid-19 epidemic year.Diabetes MellitusThe number of deaths due to diabetes increased significantly during the 2019-2020 year.
Package: covid-india
COVID-19 IndiaPython package for providing data for theCOVID-19cases in India. This can provide data both online as well as offline.requirementsFor running this, you need to havepython3installed on your system.FeaturesThis works bothonlineas well asoffline.InstallationFor windowspip install covid-indiaFor linux and Macpip3 install covid-indiaExampleAll the statesfrom covid_india import states
print(states.getdata())This returns ajsonobject which contains the datas of all the states in India.Specific statefrom covid_india import states
print(states.getdata('West Bengal'))This returns ajsonobject containing only the datas of West Bengal.Total Countfrom covid_india import states
print(states.getdata('Total'))This returns ajsonobject containing only category wise count of all the cases in India.If you use this package offline, you will get a timestamp along with the data stating when it was last updated.PyPiCOVID 19 INDIA:PyPi
Package: covid-modeling
COMODELSModels for COVID - 19For documentation, see the docstrings!
Much more to come. For help:importcomodelshelp(comodels)help(comodels.PennDeath)help(comodels.Penn)Penn Death model# import the penn modelimportmatplotlib.pyplotaspltfromcomodelsimportPennDeathhelp(PennDeath)tx=PennDeath(N=28304596,I=223,R=0,D=3,D_today=2)help(PennDeath.sir)defplot_penn(Pdp:PennDeath,n_days:int)->None:# predict the coming storm and plot itcurve,admissions=Pdp.sir(n_days)fig,ax=plt.subplots(1,3,figsize=(15,5))fork,vincurve.items():ifknotinPdp.rates.keys():ax[0].plot(v,label=k)ax[0].legend()else:ax[1].plot(v,label=k)ax[1].legend()ax[1].set_title('Hospital Resource Usage')ax[0].set_title('SIR curve')fork,vinadmissions.items():ax[2].plot(v,label=k)ax[2].legend()ax[2].set_title('Additional Resource Usage by day')fig.suptitle(f"No social distancing, total deaths ={int(max(curve['dead']))}")plt.show()plot_penn(tx,120)print(curve.keys())print(occupancy.keys())