<jupyter_start><jupyter_text>basico<jupyter_code>from keplergl import KeplerGl
import pandas as pd
df = pd.read_csv('example.csv')
df.head()
# Load kepler.gl with an empty map
map_1 = KeplerGl(height=700, data={'data1':df})
map_1
map_1.save_to_html(file_name='teste.html')<jupyter_output>Map saved to teste.html!
{'fraction_non_alphanumeric': 0.1282051282051282, 'fraction_numerical': 0.022435897435897436, 'mean_word_length': 7.942857142857143, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, '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': '253160', 'license': 'MIT', 'n_tokens_mistral': 131, 'n_tokens_neox': 127, 'n_words': 25, 'path': '09-Viz/09_kepler/00_kepler.ipynb', 'repo_name': 'abefukasawa/datascience_course', 'size': '312'}