LMIPy 0.3.30

Pythonic interface to various backend ecosystems related geospatial data.

LMIPy

The Vizzuality Ecosystem Python Interface

LMIPy is a Python library with hooks to Jupyter, backed by the Skydipper API. It provides many functions related to adding, analysing and working with open geospatial datasets.

Read the Docs

Read the docs pages.

Installation

pip install LMIPy

Use

$ python
>>> import LMIPy

Create a Dataset object based on an existing ID on default (RW) server.

>>> ds = Dataset('044f4af8-be72-4999-b7dd-13434fc4a394')
>>> print(ds)
Dataset 044f4af8-be72-4999-b7dd-13434fc4a394

Create a Layer object based on an existing ID on default (RW) server.

>>> ly = Layer(id_hash='dc6f6dd2-0718-4e41-81d2-109866bb9edd')
>>> print(ly)
Layer dc6f6dd2-0718-4e41-81d2-109866bb9edd

Create a Table object based on an existing ID.

>>> table = Table('fbf159d7-a462-4af3-8228-43ee3e3391e7')
# return the head of the table as a geopandas dataframe
>>> df = table.head(5)
# return a query of the table as a geopandas dataframe
>>> result = table.query(sql='SELECT count(*) as my_count FROM data WHERE year > 1991 and year < 1995' )

Obtain a collection of objects using a search term.

>>> col = Collection(search='tree',object_type=['dataset'], app=['gfw'],limit=5)
>>> print(col)
[Dataset 70e2549c-d722-44a6-a8d7-4a385d78565e, Dataset 897ecc76-2308-4c51-aeb3-495de0bdca79, Dataset 89755b9f-df05-4e22-a9bc-05217c8eafc8, Dataset 83f8365b-f40b-4b91-87d6-829425093da1, Dataset 044f4af8-be72-4999-b7dd-13434fc4a394]

Check the docs for more info!