Metadata-Version: 2.1
Name: covid19sweden
Version: 0.2.1
Summary: Web Scraper for Sweden COVID19 data.
Home-page: https://github.com/martinbenes1996/covid19sweden
Author: Martin Beneš
Author-email: martinbenes1996@gmail.com
License: MPL
Download-URL: https://github.com/martinbenes1996/covid19sweden/archive/0.2.1.tar.gz
Description: 
        # Web Scraper of COVID-19 data for Sweden
        
        Python package [covid19sweden](https://pypi.org/project/covid19sweden/) provides access to mortality and COVID-19 data of Sweden.
        
        The data is scraped from:
        * https://scb.se/om-scb/nyheter-och-pressmeddelanden/overdodligheten-fortsatter-att-sjunka-efter-toppen-i-april/
        
        ## Setup and usage
        
        Install from [pip](https://pypi.org/project/covid19sweden/) with
        
        ```python
        pip install covid19sweden
        ```
        
        Currently available functions are
        
        * `deaths()` fetching number of deaths
        * `fohm.regions()` and `fohm.municipalities()` fetching Covid-19 statistics in regions and municipalities.
        
        Package is regularly updated. Update with
        
        ```bash
        pip install --upgrade covid19sweden
        ```
        
        ### Covid-19 Deaths
        
        Fetch Covid-19 deaths by weeks using
        
        ```python
        import covid19sweden as SE
        
        x = SE.covid_deaths(level = 1)
        ```
        
        The data can be acquired split into regions or municipalities using granularity variable `level`
        
        ```python
        x_regions = SE.covid_deaths(level = 2)
        x_municipalities = SE.covid_deaths(level = 3)
        ```
        
        ### Deaths
        
        Overall deaths in Sweden can be fetched such as
        
        ```python
        import covid19sweden as SWE
        
        data = SWE.deaths()
        ```
        
        The function returns pandas dataframe with the columns being years and rows being deaths of each age and 
        
        **Level**
        
        Level is a setting for granularity of data
        
        1. Country level (default)
        2. State level
        3. Municipality level
        
        ```python
        import covid19sweden as SWE
        
        # country level
        x1a,x1b,x1u = SWE.deaths(level = 1)
        # state level
        x2a,x2b,x2u = SWE.deaths(level = 2)
        # municipality level
        x3a,x3b,x3u = SWE.deaths(level = 3)
        ```
        
        By default the level is 1. Level settings can be implicitly changed in the function.
        
        **Weekly**
        
        Weekly is a setting of time axis of the data.
        
        * `True` - data are by weeks
        * `False` - data are by days
        
        Default is `False`, data by days.
        
        ```python
        import covid19sweden as SWE
        
        # weekly
        xa,xb,xu = SWE.deaths(weekly = True)
        ```
        
        Given setting will implicitly change `per_gender_age = True`, even though default is `False`. This behavior is described at section [Verbose and alt](#Verbose-and-alt).
        
        Setting of `weekly` can be also implicitly changed if no data is available for given settings.
        
        **Per gender or age**
        
        The settings `per_gender_age` is controlling the deaths to be splitted into groups by gender (M,F) and age groups (mostly 0-64,65-79,80-89,90+).
        
        ```python
        import covid19sweden as SWE
        
        # weekly
        xa,xb,xu = SWE.deaths(per_gender_age = True)
        ```
        
        Setting of `per_gender_age` can be implicitly changed if no data is available for given settings.
        
        **Verbose and alt**
        
        Not for all the combinations of the parameters the data is available. E.g. for `level = 3`, only daily data without gender and age distinguishing is available. Hence to minimize error rate, implicit parameter changes are introduced.
        
        If the data for given settings is not available, a set of rules is applied to reach data:
        
        * if data is available for `not per_gender_age`, use them
        * if data is available for `not weekly`, use them
        * if data is available for `not per_gender_age`, `not_weekly`, use them
        
        Implicit parameter change is announced on stdout. It can be switched off by setting `verbose = False`.
        
        Sometimes multiple datasets with slight difference (or two conversions) are available. This is announced on stdout. Choosing an alternative data is done with `alt = True`.
        
        ### Covid-19 in regions and municipalities
        
        To fetch data in regions and municipalities, type
        
        ```python
        import covid19sweden as SWE
        
        regions = SWE.fohm.regions()
        municipalities = SWE.fohm.municipalities()
        ```
        
        Only parameter for both functions is optional `filename`,
        that saves the data to csv output file.
        
        ```python
        SWE.fohm.municipalities(filename = "output.csv")
        ```
        
        ## Commit
        
        With a single call all the data handlers are called and their outputs as well as common input (xlsx file) is stored. *Commit* is stored directory `commit_YYMMDD` (in *cwd*) unless explicitly specified.
        
        ```python
        import covid19sweden as SWE
        SWE.commit() # store all files
        ```
        
        Explicit specification of directory is done with
        
        ```python
        SWE.commit("/var/latest_data")
        ```
        
        Function will try to create the folder. It fails on existing files of the same name. Overwriting must be enabled
        
        ```python
        SWE.commit("/var/latest_data", overwrite = True)
        ```
        
        **TODO**:
        * add fohm to commit
        
        ## Contribution
        
        Developed by [Martin Benes](https://github.com/martinbenes1996).
        
        Join on [GitHub](https://github.com/martinbenes1996/covid19sweden).
        
        
        
        
Keywords: 2019-nCov,sweden,coronavirus,covid-19,covid-data,covid19-data
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Other Audience
Classifier: Topic :: Database
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
