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Hydropandas

A Python package for reading, analyzing, and writing hydrological time series from a Pandas DataFrame, with all of its wonderful features, and extended with custom methods and attributes related to hydrological time series.
https://github.com/artesiawater/hydropandas

Category: Hydrosphere
Sub Category: Ocean and Hydrology Data Access

Keywords

data groundwater hydrology observations pandas timeseries

Keywords from Contributors

flopy geopandas groundwater-modelling hydrogeology modflow pastas arctic data-management articles poster

Last synced: 1 day ago
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Package for loading hydrological time series into custom DataFrames

readme.md

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hydropandas
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HydroPandas

Hydropandas is a Python package for reading, analyzing and writing
(hydrological) timeseries.

Reading

The HydroPandas package provides convenient read functions from various sources.
The table below lists all API-accessible sources. Click a link in the first column
for the documentation. The "API available" column indicates current availability
(updated weekly).

source observations API available location
BRO Groundwater BRO Netherlands
ERA5 Meteorological ERA5 Global
GGMN Groundwater GGMN Global
GHCN Meteorological GHCN Global
KNMI Meteorological KNMI Netherlands
Lizard (Vitens) Groundwater Lizard Netherlands (Vitens)
Lizard (Rotterdam) Groundwater Lizard Rotterdam
Matroos Surface water Matroos Netherlands and neighbours
Waterconnect Groundwater Waterconnect South Australia
Waterinfo Surface water Waterinfo Netherlands

Some sources also provide files readable by HydroPandas.

source observations file format location
BRO Groundwater xml Netherlands
DINO Groundwater / surface water csv Netherlands
FEWS Groundwater / surface water xml Netherlands
KNMI Meteorological txt Netherlands
Pastastore Time series models NA NA
Waterinfo Surface water csv / zip Netherlands
Wiski (no docs available) Groundwater csv Netherlands

Install

Install the module with pip:

pip install hydropandas

For some functionality additional packages are required. Install all optional packages:

pip install hydropandas[full]

For installing in development mode, clone the repository and install by
typing pip install -e .[full] from the module root directory.

Documentation

Get in touch

Structure

The HydroPandas package allows users to store a timeseries and metadata in a
single object (Obs class). Or store a collection of timeseries with metadata
in a single object (ObsCollection class). Both inheret from a pandas DataFrame
and are extended with custom methods and attributes related to hydrological timeseries.

The Obs class

The Obs class holds the measurements and metadata for one timeseries. There are
currently 7 specific Obs classes for different types of measurements:

  • GroundwaterObs: for groundwater measurements
  • WaterQualityObs: 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.
Each Obs object also contains specific methods to read data from specific sources.

The ObsCollection class

The ObsCollection class hold the data for a collection of Obs classes, e.g.
10 timeseries of the groundwater level in a certain area. The
ObsCollection is essentialy 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 that holds the
measurements. It's recommended to use one ObsCollection per observation type — for
example, group 10 GroundwaterObs in one collection and 5 PrecipitationObs in another.

More information on dealing with Obs and ObsCollection objects in the documentation

Authors

  • Onno Ebbens, Artesia
  • Ruben Caljé, Artesia
  • Davíd Brakenhoff, Artesia
  • Martin Vonk, Artesia

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Committers metadata

Last synced: 6 days ago

Total Commits: 1,526
Total Committers: 12
Avg Commits per committer: 127.167
Development Distribution Score (DDS): 0.419

Commits in past year: 241
Committers in past year: 6
Avg Commits per committer in past year: 40.167
Development Distribution Score (DDS) in past year: 0.382

Name Email Commits
OnnoEbbens o****s@g****m 886
dbrakenhoff d****f@a****l 287
Martin Vonk v****t@g****m 256
Mattijs Borst m****t@c****l 41
Hendrik Meuwese 1****W 17
Tom Hottentot t****t@r****m 10
Ruben Caljé r****e@a****l 10
Floris van 't Klooster 6****r 8
Artesia Water 3****r 7
anouksprong a****g@v****l 2
Thomas Berends t****s@h****m 1
Justin Jent j****r@g****m 1

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Issue and Pull Request metadata

Last synced: 3 days ago

Total issues: 127
Total pull requests: 222
Average time to close issues: 4 months
Average time to close pull requests: 5 days
Total issue authors: 23
Total pull request authors: 12
Average comments per issue: 1.81
Average comments per pull request: 0.93
Merged pull request: 196
Bot issues: 0
Bot pull requests: 1

Past year issues: 16
Past year pull requests: 25
Past year average time to close issues: 3 days
Past year average time to close pull requests: 8 days
Past year issue authors: 9
Past year pull request authors: 7
Past year average comments per issue: 2.13
Past year average comments per pull request: 1.6
Past year merged pull request: 19
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/artesiawater/hydropandas

Top Issue Authors

  • OnnoEbbens (55)
  • martinvonk (19)
  • dbrakenhoff (16)
  • HMEUW (9)
  • MattBrst (4)
  • rubencalje (3)
  • jvansijl (2)
  • Florisklooster (2)
  • JaccoHoogewoud (2)
  • ArtemisRo (2)
  • markvdbrink (1)
  • Rickboeve1002 (1)
  • SOsinga (1)
  • TomHottentot (1)
  • thomas-wsbd (1)

Top Pull Request Authors

  • OnnoEbbens (129)
  • dbrakenhoff (34)
  • martinvonk (22)
  • Florisklooster (8)
  • HMEUW (8)
  • MattBrst (7)
  • rubencalje (6)
  • ArtesiaWater (2)
  • tberends (2)
  • anouksprong (2)
  • TomHottentot (1)
  • dependabot[bot] (1)

Top Issue Labels

  • enhancement (17)
  • bug (5)
  • code quality (3)
  • question (2)
  • help wanted (1)
  • documentation (1)
  • wontfix (1)

Top Pull Request Labels

  • enhancement (18)
  • bug (4)
  • code quality (3)
  • javascript (1)
  • dependencies (1)

Package metadata

proxy.golang.org: github.com/artesiawater/hydropandas

proxy.golang.org: github.com/ArtesiaWater/hydropandas

pypi.org: hydropandas

Module by Artesia for loading observation data into custom DataFrames.

  • Homepage:
  • Documentation: https://hydropandas.readthedocs.io/
  • Licenses: MIT License
  • Latest release: 0.18.1 (published 6 months ago)
  • Last Synced: 2026-08-11T12:07:39.024Z (2 days ago)
  • Versions: 48
  • Dependent Packages: 3
  • Dependent Repositories: 1
  • Downloads: 2,092 Last month
  • Rankings:
    • Dependent packages count: 3.156%
    • Downloads: 8.785%
    • Average: 11.183%
    • Dependent repos count: 21.607%
  • Maintainers (2)

Dependencies

docs/requirements.txt pypi
  • Ipython *
  • docutils <0.18
  • flopy *
  • ipykernel *
  • nbsphinx *
  • nbsphinx_link *
  • netCDF4 *
  • pastastore *
  • sphinx_rtd_theme *
  • tqdm *
  • xarray *
requirements.txt pypi
  • bokeh *
  • branca *
  • flopy *
  • folium *
  • geopandas *
  • ipykernel *
  • lxml *
  • matplotlib >=3.0
  • nbconvert *
  • nbformat *
  • netCDF4 ==1.5.7
  • numpy >=1.15
  • pandas *
  • pastas *
  • pastastore *
  • pyproj *
  • requests *
  • scipy >=1.2
  • shapely *
  • tqdm *
  • xarray *
  • zeep *
setup.py pypi
  • scipy *

Score: 14.738816624732335