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: about 15 hours ago
JSON representation

Repository metadata

Package for loading hydrological time series into custom DataFrames

Host: GitHub
URL: https://github.com/artesiawater/hydropandas
Owner: ArtesiaWater
License: mit
Created: 2019-06-28T09:58:59.000Z (about 7 years ago)
Default Branch: dev
Last Pushed: 2026-08-27T14:39:28.000Z (7 days ago)
Last Synced: 2026-08-27T21:08:43.789Z (7 days ago)
Topics: data, groundwater, hydrology, observations, pandas, timeseries
Language: Python
Homepage: https://hydropandas.readthedocs.io
Size: 51.4 MB
Stars: 74
Watchers: 5
Forks: 12
Open Issues: 30
Releases: 54
Metadata Files:
- Readme: readme.md
- License: LICENSE

readme.md

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

Documentation is provided on the dedicated website
hydropandas.readthedocs.io
Examples are available in the examples directory on the documentation website
View and edit the example notebooks of hydropandas in
GitHub Codespaces

Get in touch

Questions on HydroPandas ("How can I?") can be asked and answered on Github Discussions.
Bugs, feature requests and other improvements can be posted as Github Issues.
Find out how to contribute to HydroPandas at our Contribution page.

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

Owner metadata

Name: Artesia Water
Login: ArtesiaWater
Email:
Kind: user
Description: Artesia adviseert bij hydrologische vraagstukken. We zijn gespecialiseerd in het programmeren van modellen in Python, Matlab en andere bekende programmeertalen.
Website: http://www.artesia-water.nl
Location: Schoonhoven, The Netherlands
Twitter:
Company: Artesia Water
Icon url: https://avatars.githubusercontent.com/u/31697400?u=a5a6fc31ec93c07853dd53835936fd90c44f7483&v=4
Repositories: 13
Last ynced at: 2024-04-24T04:06:10.080Z
Profile URL: https://github.com/ArtesiaWater

GitHub Events

Total

Create event: 41
Delete event: 33
Issue comment event: 105
Issues event: 54
Pull request event: 69
Pull request review comment event: 43
Pull request review event: 81
Push event: 242
Release event: 12
Watch event: 15

Last Year

Create event: 6
Delete event: 9
Issue comment event: 21
Issues event: 11
Pull request event: 13
Pull request review comment event: 16
Pull request review event: 24
Push event: 65
Release event: 2
Watch event: 2

Committers metadata

Last synced: 14 days ago

Total Commits: 1,534
Total Committers: 12
Avg Commits per committer: 127.833
Development Distribution Score (DDS): 0.418

Commits in past year: 211
Committers in past year: 6
Avg Commits per committer in past year: 35.167
Development Distribution Score (DDS) in past year: 0.341

Name	Email	Commits
OnnoEbbens	o**s@g**m	893
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	11
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

Committer domains:

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 131
Total pull requests: 225
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: 1.82
Average comments per pull request: 0.94
Merged pull request: 199
Bot issues: 0
Bot pull requests: 1

Past year issues: 20
Past year pull requests: 25
Past year average time to close issues: 3 days
Past year average time to close pull requests: 9 days
Past year issue authors: 9
Past year pull request authors: 6
Past year average comments per issue: 2.1
Past year average comments per pull request: 1.72
Past year merged pull request: 21
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 (58)
martinvonk (19)
dbrakenhoff (16)
HMEUW (9)
MattBrst (4)
rubencalje (3)
jvansijl (2)
Florisklooster (2)
JaccoHoogewoud (2)
ArtemisRo (2)
Arjanvw (2)
markvdbrink (1)
Rickboeve1002 (1)
SOsinga (1)
TomHottentot (1)

Top Pull Request Authors

OnnoEbbens (131)
dbrakenhoff (34)
martinvonk (22)
Florisklooster (8)
HMEUW (8)
MattBrst (7)
rubencalje (6)
TomHottentot (2)
ArtesiaWater (2)
tberends (2)
anouksprong (2)
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

Total packages: 3
Total downloads:
- pypi: 2,419 last-month
Total dependent packages: 3 (may contain duplicates)
Total dependent repositories: 1 (may contain duplicates)
Total versions: 143
Total maintainers: 2

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

Homepage:
Documentation: https://pkg.go.dev/github.com/artesiawater/hydropandas#section-documentation
Licenses: mit
Latest release: v0.19.0 (published 13 days ago)
Last Synced: 2026-09-02T03:45:08.417Z (1 day ago)
Versions: 47
Dependent Packages: 0
Dependent Repositories: 0
Rankings:
- Dependent packages count: 5.401%
- Average: 5.583%
- Dependent repos count: 5.764%

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

Homepage:
Documentation: https://pkg.go.dev/github.com/ArtesiaWater/hydropandas#section-documentation
Licenses: mit
Latest release: v0.19.0 (published 13 days ago)
Last Synced: 2026-09-02T00:39:23.832Z (1 day ago)
Versions: 47
Dependent Packages: 0
Dependent Repositories: 0
Rankings:
- Dependent packages count: 5.401%
- Average: 5.583%
- Dependent repos count: 5.764%

pypi.org: hydropandas

Module by Artesia for loading observation data into custom DataFrames.

Homepage:
Documentation: https://hydropandas.readthedocs.io/
Licenses: MIT License
Latest release: 0.19.0 (published 14 days ago)
Last Synced: 2026-09-01T23:34:07.982Z (1 day ago)
Versions: 49
Dependent Packages: 3
Dependent Repositories: 1
Downloads: 2,419 Last month
Rankings:
- Dependent packages count: 3.156%
- Downloads: 8.785%
- Average: 11.183%
- Dependent repos count: 21.607%
Maintainers (2)
- dbrakenhoff
- Onno

Dependencies

pyproject.toml pypi

bokeh *
branca *
contextily *
folium *
geopandas *
matplotlib *
openpyxl *
pandas *
pastastore >=1.10.2
pyproj *
requests *
rws-ddlpy *
scipy *
tqdm *

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Score: 14.922884352300956

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