Module by Artesia for loading observation data into custom DataFrames.
Project description
hydropandas
The HydroPandas package allows users to store observation data at multiple locations in a single object (ObsCollection). An ObsCollection is a pandas DataFrame extended with custom methods and attributes related to hydrological timeseries. The HydroPandas package also provides convenient read functions for Dutch hydrological data from:
- BRO
- DINO
- FEWS PI-XML
- KNMI
- MODFLOW groundwater models
- IMOD groundwater models
- Pastastore
- waterinfo
- WISKI csv files
Installation
Install the module with pip:
pip install hydropandas
Hydropandas requires numpy
, scipy
, matplotlib
, pandas
, requests
and zeep
.
For some functionality additional packages are required:
geopandas
: for dealing with shapefilespastastore
: for reading or storing data from PastaStorebokeh
,branca
,folium
: for interactive mapsflopy
: for reading data from MODFLOW modelsxarray
: for loading data from REGIS
For installing in development mode, clone the repository and install by
typing pip install -e .
from the module root directory.
For installing all the optional packages use pip install -e .[full]
If you have trouble installing HydroPandas, refer to the Dependencies section below.
Example usage
Importing a single DINO csv file:
import hydropandas as hpd
fname = './tests/data/2019-Dino-test/Grondwaterstanden_Put/B33F0080001_1.csv'
gw = hpd.GroundwaterObs.from_dino(fname=fname)
Or for a zipfile:
import hydropandas as hpd
dinozip = './tests/data/2019-Dino-test/dino.zip'
dino_gw = hpd.read_dino(dirname=dinozip,
subdir='Grondwaterstanden_Put',
suffix='1.csv',
ObsClass=hpd.GroundwaterObs,
keep_all_obs=False)
The Obs class
The Obs class holds the measurements and metadata for one timeseries. There are currently 5 specific Obs classes for different types of measurements:
- GroundwaterObs: for groundwater measurements
- GroundwaterQualityObs: for groundwater quality measurements
- WaterlvlObs: for surface water level measurements
- ModelObs: for "observations" from a MODFLOW model
- MeteoObs: for meteorological observations
- PrecipitationObs: for precipitation observations, subclass of MeteoObs
- EvaporationObs: for evaporation observations, subclass of MeteoObs
Each of these Obs classes is essentially a pandas DataFrame with additional methods and attributes related to the type of measurement that it holds. The classes also contain specific methods to read data from specific sources.
The ObsCollection class
The ObsCollection class, as the name implies, represents a collection of Obs classes, e.g. 10 timeseries of the groundwater level in a certain area. The ObsCollection is also a pandas DataFrame in which each timeseries is stored in a different row. Each row contains metadata (e.g. latitude and longitude of the observation point) and the Obs object (DataFrame) that holds the measurements. It is recommended to let an ObsCollection contain only one Obs type, e.g. to create an ObsCollection for 10 GroundwaterObs, and a separate ObsCollection for 5 PrecipitationObs.
Like the Obs class, the ObsCollection class contains a bunch of methods for reading data from different sources. See the next section for supported data sources.
Dependencies
Hydropandas (indirectly) uses some packages that cannot be installed
automatically with pip
on Windows. These packages are:
- GDAL
- Fiona
- Shapely
If you do not have these packages already it is recommended to first try
installing them with conda install <pkg>
. Otherwise, read the instructions
below how to install them manually.
Download the packages from Christoph Gohlke's website. Use CTRL+F to find the download link on the page. Be sure to download the correct version of the package. The Python version should match your Python version. Also the architecture should match (i.e. 64bits vs 32bits). For example:
- GDAL-3.1.4-cp38-cp38-win_amd64.whl
This is the GDAL version for Python 3.8 (as can be seen from the cp38 in the name), for 64-bits Python (as derived from the amd64 in the name).
Once you have downloaded the correct files, navigate to the directory in which you saved your downloads. Now type the following commands (the order is important):
pip install GDAL-3.1.4-cp38-cp38-win_amd64.whl
pip install Fiona-1.8.17-cp38-cp38-win_amd64.whl
pip install Shapely-1.7.1-cp38-cp38-win_amd64.whl
After you've done this you can install hydropandas using
pip install hydropandas
.
Authors
- Onno Ebbens, Artesia
- Ruben Caljé, Artesia
- Davíd Brakenhoff, Artesia
- Martin Vonk, Artesia
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