geo-explorer
Explore geodata interactively with a file browser.
Opprettet av: ort ort@ssb.no
To install, use either:
poetry add geo-explorer
Or:
pip install geo-explorer
GeoExplorer
It's best to run the app in the terminal.
Create a simple python file:
from geo_explorer import GeoExplorer
from gcsfs import GCSFileSystem
DELT_KART = "ssb-areal-data-delt-kart-prod"
YEAR = 2025
GeoExplorer(
start_dir=f"{DELT_KART}/analyse_data/klargjorte-data/{YEAR}",
favorites=[
f"{DELT_KART}/analyse_data/klargjorte-data/{YEAR}",
f"{DELT_KART}/visualisering_data/klargjorte-data/{YEAR}/parquet",
],
center=(59.91740845, 10.71394444),
zoom=13,
file_system=GCSFileSystem(),
port=3000,
).run()
And run it:
poetry run python my_file.py
# or
python my_file.py
Export as code
The export button can be used to "save" your map. Copy the printed code and paste it into a new file. Running this file will give you an app with the same bounds, data and coloring.
Starting the app with data loaded, filtered and colored
Here is an example of a GeoExplorer app where data is loaded, filtered and colored:
import sgis as sg
entur_path = f"{DELT_KART}/analyse_data/klargjorte-data/{YEAR}/ENTUR_Holdeplasser_punkt_p{YEAR}_v1.parquet"
# Create a custom GeoDataFrame to add to the map
jernbanetorget = sg.to_gdf([10.7535581, 59.9110967], crs=4326).to_crs(25833)
jernbanetorget.geometry = jernbanetorget.buffer(500)
GeoExplorer(
start_dir=f"{DELT_KART}/analyse_data/klargjorte-data/{YEAR}",
favorites=[
f"{DELT_KART}/analyse_data/klargjorte-data/{YEAR}",
f"{DELT_KART}/visualisering_data/klargjorte-data/{YEAR}/parquet",
],
data={
"jernbanetorget_500m": jernbanetorget,
entur_path: "kjoeretoey != 'fly'",
},
column="kjoeretoey",
color_dict={
"jernbane": "darkgreen",
"buss": "red",
"trikk": "deepskyblue",
"tbane": "yellow",
"baat": "navy",
},
center=(59.91740845, 10.71394444),
zoom=13,
file_system=GCSFileSystem(),
port=3000,
).run()
The 'data' argument can be either:
- a list of file paths
- a dict with labels as keys and GeoDataFrames as values
- a dict with file paths as keys and filter function (or None) as value (note that the filter function must be formated as a string!)
Set the 'column' argument to color the geometries.
Optionally specify what colors with the 'color_dict' argument (with column values as dict keys and color codes (hex) or named colors (https://matplotlib.org/stable/gallery/color/named_colors.html) as dict values).
Filter functions
Filtering data can be done in the GeoExplorer init, as shown above, or in the app.
Filter functions can be:
- polars expression or an iterable of such, e.g.: (pl.col("FYLKE") != "50", pl.col("FYLKE") != "03")
- lambda functions accepted by pandas.loc, e.g. lambda x: x["kjoeretoey"] != "fly"
- queries accepted by pandas.query, e.g. kjoeretoey != "fly"
Note that the filter functions must be wrapped in quotation marks ("") if used in the GeoExplorer init.
For large datasets, the polars approach might be noticeably faster, both because polars is faster and because the data is stored as polars.DataFrames and converted to pandas and back if the polars filtering fails.
Local files
For local files, use the LocalFileSystem class, which simply implements glob and ls methods based on the standard library (os and glob).
from geo_explorer import GeoExplorer
from geo_explorer import LocalFileSystem
GeoExplorer(
start_dir="ssb-areal-data-delt-kart-prod/analyse_data/klargjorte-data/2025",
file_system=GCSFileSystem(),
).run()
Other file systems can be used, as long as it acts like fsspec's AbstractFileSystem and implement the methods ls and glob. The methods should take the argument 'detail', which, if set to True, will return a dict for each listed path with the keys "updated" (timestamp), "size" (bytes), "name" (full path) and "type" ("directory" or "file").
Developer information
Git LFS
The data in the testdata directory is stored with Git LFS.
Make sure git-lfs is installed and that you have run the command git lfs install
at least once. You only need to run this once per user account.
Dependencies
Poetry is used for dependency management. Install poetry and run the command below from the root directory to install the dependencies.
poetry install -E test --no-root
Tests
Use the following command from the root directory to run the tests:
poetry run pytest # from root directory
For VS Code there are extensions for opening a python script as Jupyter Notebook, for example: Jupytext for Notebooks.
Code quality
Run 'ruff' on all files with safe fixes:
poetry run ruff check --fix .
Formatting
Format the code with black and isort by running the following command from the
root directory:
poetry run black .
poetry run isort .
Pre-commit hooks
We are using pre-commit hooks to make sure the code is correctly formatted and consistent before committing. Use the following command from the root directory in the repo to install the pre-commit hooks:
poetry run pre-commit install
It then checks the changed files before committing. You can run the pre-commit checks on all files by using this command:
poetry run pre-commit run --all-files
Documentation
To generate the API-documentation locally, run the following command from the root directory:
poetry run sphinx-build -W docs docs/_build
Then open the file docs/_build/index.html.
To check and run the docstrings examples, run this command:
poetry run xdoctest --command=all ./src/sgis
Contributing
Contributions are very welcome. To learn more, see the Contributor Guide.
License
Distributed under the terms of the MIT license, SSB sgis is free and open source software.
Issues
If you encounter any problems, please file an issue along with a detailed description.
Credits
This project was generated from Statistics Norway's SSB PyPI Template.
1 maintainer
Metadata
1 maintainer
Release files for geo-explorer 0.9.23
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