H3-Pandas ⬢ 🐼

Integrates H3 with GeoPandas and Pandas.

⬢ Try it out ⬢

Installation

pip

pip install h3pandas

conda

[

]()

conda install -c conda-forge h3pandas

Usage examples

H3 API

h3pandas automatically applies H3 functions to both Pandas Dataframes and GeoPandas Geodataframes

# Prepare data
>>> import pandas as pd
>>> import h3pandas
>>> df = pd.DataFrame({'lat': [50, 51], 'lng': [14, 15]})

>>> resolution = 10
>>> df = df.h3.geotoh3(resolution)
>>> df
| h3_10           |   lat |   lng | |:----------------|------:|------:| | 8a1e30973807fff |    50 |    14 | | 8a1e2659c2c7fff |    51 |    15 |
>>> df = df.h3.h3togeo_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.

# 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)})
>>> })

# Aggregate values by their location and sum
>>> df = df.h3.geotoh3_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.h3toparent_aggregate(2)
| h3_02           |   value | geometry        | |:----------------|--------:|:----------------| | 821e37fffffffff |    9035 | POLYGON ((...)) | | 821f1ffffffffff |    1040 | POLYGON ((...)) |