<jupyter_start><jupyter_text>Point Patterns<jupyter_code>import numpy as np
from pysal.explore.pointpats import PointPattern
import libpysal as ps
%matplotlib inline
import matplotlib.pyplot as plt
import geopandas as gpd
file = "https://opendata.arcgis.com/datasets/e295d0fe5def4102b42bdab776fe67d0_0.zip"
df = gpd.read_file(file)
df.head()
pp = PointPattern(points) #create a point pattern "pp" from list
pp.points 
from pysal.explore.pointpats.centrography import hull, mbr, mean_center, weighted_mean_center, manhattan_median, std_distance,euclidean_median,ellipse
mc = mean_center(df.geometry)
mc<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.08399366085578447, 'fraction_numerical': 0.028526148969889066, 'mean_word_length': 7.777777777777778, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '494614', 'license': 'MIT', 'n_tokens_mistral': 250, 'n_tokens_neox': 236, 'n_words': 50, 'path': 'notebooks/Point Pattern Analysis.ipynb', 'repo_name': 'minsait-geospatial/geo-binder', 'size': '631'}