<jupyter_start><jupyter_text>Mygeopackage  Create an interactive map<jupyter_code>from mygeopackage import Map
m = Map()
m<jupyter_output><empty_output><jupyter_text>Use satellite google map as base map<jupyter_code>m = Map(google_map='HYBRID')
m<jupyter_output><empty_output><jupyter_text>Change Layout<jupyter_code>m = Map(height = '500px')
m<jupyter_output><empty_output><jupyter_text>Change default center and zoom level<jupyter_code>m = Map(center = [23,121], zoom = 7)
m<jupyter_output><empty_output><jupyter_text>Read geojson and convert it to numpy array<jupyter_code>from mygeopackage import Geo
geojson = Geo(r'https://github.com/yungming0119/mygeopackage/blob/main/docs/notebooks/data/sample_points.geojson?raw=true')<jupyter_output><empty_output><jupyter_text>Access CRS of the data<jupyter_code>geojson.crs<jupyter_output><empty_output><jupyter_text>Access array of the data<jupyter_code>geojson.data<jupyter_output><empty_output><jupyter_text>Access fields of the data<jupyter_code>geojson.attributes
from mygeopackage.unsupervised import Cluster, k_means
cluster_results = Cluster(geojson.data[0:100])
k_means(10,[0,1],cluster_results,3)
cluster_results.show()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11037344398340249, 'fraction_numerical': 0.018257261410788383, 'mean_word_length': 11.829787234042554, 'pattern_counts': {'":': 0, '<': 33, '<?xml version=': 0, '>': 33, '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': '8', 'dir': 'jupyter-structured-clean-dedup', 'id': '380315', 'license': 'MIT', 'n_tokens_mistral': 479, 'n_tokens_neox': 453, 'n_words': 66, 'path': 'docs/notebooks/mygeopackage_demo.ipynb', 'repo_name': 'yungming0119/mygeopackage', 'size': '1205'}