<jupyter_start><jupyter_text>- https://www.twilio.com/blog/2017/08/geospatial-analysis-python-geojson-geopandas.html- https://github.com/lesley2958/twilio-geospatial<jupyter_code>from shapely.geometry import Point, Polygon
p1 = Point(0,0)
print(p1)
print(p1 == (0,0))
print(type(p1))
polygon = Polygon([(0,0), (1,1), (1,0)])<jupyter_output><empty_output><jupyter_text>https://github.com/ContinuumIO/anaconda-issues/issues/9449<jupyter_code>import geopandas as gpd
states = gpd.read_file('states.geojson')
states.head()
import geojsonio<jupyter_output><empty_output><jupyter_text>once display is run, browser will open interface<jupyter_code>geojsonio.display(states)
contents = open('map.geojson').read()
print(contents)
geojsonio.display(contents)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15552699228791775, 'fraction_numerical': 0.03598971722365039, 'mean_word_length': 8.987179487179487, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 3, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '157580', 'license': 'BSD-2-Clause', 'n_tokens_mistral': 317, 'n_tokens_neox': 303, 'n_words': 36, 'path': 'geospatial/geopandas.ipynb', 'repo_name': 'shawnngtq/data-science', 'size': '778'}