Metadata-Version: 2.1
Name: h3pandas
Version: 0.2.2
Summary: Integration of H3 and GeoPandas
Home-page: https://github.com/DahnJ/H3-Pandas
Author: Dahn
Author-email: dahnjahn@gmail.com
License: MIT
Download-URL: https://github.com/DahnJ/H3-Pandas/archive/refs/tags/0.2.2.tar.gz
Description: <img align="left" src="https://i.imgur.com/OH8DoTA.png" alt="H3 Logo" width="500">
        
        
        &nbsp;
        
        # H3-Pandas ⬢ 🐼
        Integrates [H3](https://github.com/uber/h3-py) with  [GeoPandas](https://github.com/geopandas/geopandas)
        and [Pandas](https://github.com/pandas-dev/pandas).
        
        [![image](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DahnJ/H3-Pandas/blob/master/notebook/00-intro.ipynb)
        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/DahnJ/H3-Pandas/HEAD?filepath=%2Fnotebook%2F00-intro.ipynb)
        [![image](https://img.shields.io/pypi/v/h3pandas.svg)](https://pypi.python.org/pypi/h3pandas)
        [![image](https://pepy.tech/badge/h3pandas)](https://pepy.tech/project/h3pandas)
        [![Anaconda-Server Badge](https://anaconda.org/dahn/h3pandas/badges/downloads.svg)](https://anaconda.org/dahn/h3pandas)
        [![image](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
        [![Documentation Status](https://readthedocs.org/projects/pip/badge/?version=stable)](https://pip.pypa.io/en/stable/?badge=stable)
        
        &nbsp;
        
        
        ---
        
        <h3 align="center">
          ⬢ <a href="https://mybinder.org/v2/gh/DahnJ/H3-Pandas/HEAD?filepath=%2Fnotebook%2F00-intro.ipynb">Try it out</a> ⬢
        </h3>
        
        ---
        <p align="center">
            <a href="https://github.com/DahnJ/H3-Pandas"><img src="https://i.imgur.com/GZWsC8G.gif" alt="example usage" width="450"></a>
        </p>
        
        
        ## Installation
        ### pip
        ```bash
        pip install h3pandas
        ```
        
        ### conda
        ```bash
        conda install -c conda-forge h3pandas
        ```
        
        ## Usage examples
        
        ### H3 API
        `h3pandas` automatically applies H3 functions to both Pandas Dataframes and GeoPandas Geodataframes
        
        ```python
        # Prepare data
        >>> import pandas as pd
        >>> import h3pandas
        >>> df = pd.DataFrame({'lat': [50, 51], 'lng': [14, 15]})
        ```
        
        ```python
        >>> resolution = 10
        >>> df = df.h3.geo_to_h3(resolution)
        >>> df
        
        | h3_10           |   lat |   lng |
        |:----------------|------:|------:|
        | 8a1e30973807fff |    50 |    14 |
        | 8a1e2659c2c7fff |    51 |    15 |
        
        >>> df = df.h3.h3_to_geo_boundary()
        >>> df
        
        | h3_10           |   lat |   lng | geometry        |
        |:----------------|------:|------:|:----------------|
        | 8a1e30973807fff |    50 |    14 | POLYGON ((...)) |
        | 8a1e2659c2c7fff |    51 |    15 | POLYGON ((...)) |
        ```
        
        ### H3-Pandas Extended API
        `h3pandas` also provides some extended functionality out-of-the-box, 
        often simplifying common workflows into a single command.
        
        ```python
        # Set up data
        >>> import numpy as np
        >>> import pandas as pd
        >>> np.random.seed(1729)
        >>> df = pd.DataFrame({
        >>>   'lat': np.random.uniform(50, 51, 100),
        >>>   'lng': np.random.uniform(14, 15, 100),
        >>>   'value': np.random.poisson(100, 100)})
        >>> })
        ```
        
        ```python
        # Aggregate values by their location and sum
        >>> df = df.h3.geo_to_h3_aggregate(3)
        >>> df
        
        | h3_03           |   value | geometry        |
        |:----------------|--------:|:----------------|
        | 831e30fffffffff |     102 | POLYGON ((...)) |
        | 831e34fffffffff |     189 | POLYGON ((...)) |
        | 831e35fffffffff |    8744 | POLYGON ((...)) |
        | 831f1bfffffffff |    1040 | POLYGON ((...)) |
        
        # Aggregate to a lower H3 resolution
        >>> df.h3.h3_to_parent_aggregate(2)
        
        | h3_02           |   value | geometry        |
        |:----------------|--------:|:----------------|
        | 821e37fffffffff |    9035 | POLYGON ((...)) |
        | 821f1ffffffffff |    1040 | POLYGON ((...)) |
        ```
        
        
        ### Further examples
        For more examples, see the 
        [example notebooks](https://nbviewer.jupyter.org/github/DahnJ/H3-Pandas/tree/master/notebook/).
        
        ## API
        For a full API documentation and more usage examples, see the 
        [documentation](https://h3-pandas.readthedocs.io/en/latest/).
        
        ## Development
        This package is under active development, **suggestions and contributions are very welcome**!
        
        In particular, the next steps are:
        - [ ] Improve documentation, examples
        - [ ] Greater coverage of the H3 API
        
        Additional possible directions
        - [ ] Allow for alternate h3-py APIs such as [memview_int](https://github.com/uber/h3-py#h3apimemview_int)
        - [ ] Performance improvements through [Cythonized h3-py](https://github.com/uber/h3-py/pull/147)
        - [ ] [Dask](https://github.com/dask/dask) integration trough [dask-geopandas](https://github.com/geopandas/dask-geopandas) (experimental as of now)
        
Keywords: python,h3,geospatial,geopandas,pandas,integration,hexagons-are-bestagons
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: docs
