Metadata-Version: 2.1
Name: python-sa-gwdata
Version: 0.4.1
Summary: Unofficial Python package to ease access to groundwater data in South Australia
Home-page: https://github.com/kinverarity1/python-sa-gwdata
Author: Kent Inverarity
Author-email: kinverarity@hotmail.com
License: MIT
Description: # python-sa-gwdata
        
        ``sa_gwdata`` is a Python package to ease access to groundwater data in South Australia.
        It provides access to JSON data from the 
        [WaterConnect Groundwater Data](https://www.waterconnect.sa.gov.au/Systems/GD/Pages/Default.aspx) website, 
        and also provides some well data from [SARIG](https://minerals.sarig.sa.gov.au/QuickSearch.aspx).
        There are simple methods to easily turn this data into pandas DataFrames.
        
        This is an unofficial hobby project of mine. Use at your own risk... or perhaps reward? :-)
        
        ## Install
        
        ```posh
        > pip install python-sa-gwdata
        ```
        
        ## How to use
        
        Check out the [documentation](https://python-sa-gwdata.readthedocs.io/en/latest/index.html), and 
        some tutorial Jupyter Notebooks in the [notebooks](notebooks) folder.
        
        Start a web session with Groundwater Data:
        
        ```python
        >>> import sa_gwdata
        >>> session = sa_gwdata.WaterConnectSession()
        ```
        
        On initialisation it downloads some summary information.
        
        ```python
        >>> session.networks
        {'ANGBRM': 'Angas Bremer PWA',
         'AW_NP': 'Alinytjara Wilurara Non-Prescribed Area',
         'BAROOTA': 'Baroota PWRA',
         'BAROSSA': 'Barossa PWRA',
         'BAROSS_IRR': 'Barossa irrigation wells salinity monitoring',
         'BERI_REN': 'Berri and Renmark Irrigation Areas',
         'BOT_GDNS': 'Botanic Gardens wetlands',
         'CENT_ADEL': 'Central Adelaide PWA',
         'CHOWILLA': 'Chowilla Floodplain',
         ...
        }
        ```
        
        With this information we can make some direct REST calls:
        
        ```python
        >>> r = session.get("GetObswellNetworkData", params={"Network": "CENT_ADEL"})
        >>> r.df.head(5)
        	aq_mon	chem	class	dhno	drill_date	lat	latest_open_date	latest_open_depth	latest_sal_date	latest_swl_date	...	pwa	replaceunitnum	sal	salstatus	stat_desc	swl	swlstatus	tds	water	yield
        0	Tomw(T2)	Y	WW	27382	1968-02-07	-34.764662	1992-02-20	225.00	2013-09-02	2018-09-18	...	Central Adelaide	NaN	Y	C	OPR	3.47	C	3620.0	Y	2.00
        1	Qhcks	N	WW	27437	1963-01-01	-34.800905	1963-01-01	6.40	1984-02-01	1986-03-05	...	Central Adelaide	NaN	Y	H	NaN	5.86	H	1121.0	Y	NaN
        2	Tomw(T1)	Y	WW	27443	1972-04-20	-34.811124	2014-04-01	0.00	1991-10-09	2003-07-04	...	Central Adelaide	NaN	Y	H	BKF	NaN	H	2030.0	Y	5.00
        3	Tomw(T1)	Y	WW	27504	1978-02-28	-34.779893	1978-02-28	144.50	2016-04-06	2011-09-18	...	Central Adelaide	NaN	Y	H	OPR	11.21	H	2738.0	Y	0.00
        4	Tomw(T1)	Y	WW	27569	1975-01-01	-34.891250	1975-07-09	131.10	1986-11-13	1988-09-21	...	Central Adelaide	NaN	Y	H	BKF	9.90	H	42070.0	Y	12.50
        ```
        
        Get water levels:
        
        ```python
        >>> wl = session.get("GetWaterLevelDetails", params={"DHNO": 188444}).df
        >>> wl.head(5)
        	anomalous_ind	data_source_code	measured_during	obs_date	pumping_ind	rswl	standing_water_level
        0	N	DEWNR	D	2002-01-28	N	-8.12	15.08
        1	N	DEWNR	M	2002-03-06	N	-12.50	19.46
        2	N	DEWNR	M	2002-10-02	N	-3.43	10.39
        3	N	DEWNR	M	2003-03-04	N	-11.69	18.65
        4	N	DEWNR	M	2003-09-27	N	-1.93	8.89
        ```
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
