Metadata-Version: 2.4
Name: stadincijfers
Version: 0.2.3
Summary: A python package to make data from stadincijfers easily available for data scientists. 
Home-page: https://github.com/Team-Data-Antwerpen/stadincijfers.py
Author: Kay Warrie, Sofie Cromheeke
Author-email: kaywarrie@gmail.com, sofie.cromheeke@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=2.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

Stad in Cijfers, python API
================

Purpose
----

A python package to make data from stadincijfers easely available for data scientists. 

Intro
-----

Via the website 'Stad in cijfers' you can consult statistical data on various themes. In principle for the city of Antwerp, all data on 'Stad in cijfers' is open data and can therefore be used freely, unless stated otherwise.

Many local goverments in Flanders have a website like this:

- Gent: https://gent.buurtmonitor.be
- Antwerp: https://stadincijfers.antwerpen.be/databank
- The provinces: https://provincies.incijfers.be

Other websites that use the same platform:
- IMA-Atlas: https://atlas.ima-aim.be/
- Bevolkingsonderzoek: https://bevolkingsonderzoek.incijfers.be/

Installation:
--------------

from [pypi](https://pypi.org/project/stadincijfers/): 

    pip install stadincijfers

or from sources: 
    
    git clone https://github.com/warrieka/stadincijfers.py
    cd stadincijfers.py
    pip install -r requirements.txt
    pip install .

Usage:
-----

1) List periodlevels in the SIC site of Antwerp. 
```python
    from stadincijfers import stadincijfers
    sic = stadincijfers("antwerpen") #or gent or provincies or ima-atlas or bevolkingsonderzoek or url
    sic.periodlevels() #=> get all periodslevels
```

2) Export excel: 
```python
    from stadincijfers import stadincijfers
    sic = stadincijfers("antwerpen") #or gent or provincies or url
    bevdicht = sic.selectiontableasDataframe('bevdicht', geolevel='sector', periodlevel='year', period=2022)
    bevdicht.to_excel('data\\bevdicht2022.xlsx') # save to excel
```


For more see example jupyter notebook: [example_usage.ipynb](example_usage.ipynb)
