<jupyter_start><jupyter_text>Import Data<jupyter_code>import pandas as pd 
# get data 
from pycaret.datasets import get_data
df = get_data('insurance')
# shape 
df.shape
# info 
df.info()
# summary stats 
df.describe()
# summary stats 
df.describe(include='all')
from pycaret.regression import *<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11076923076923077, 'fraction_numerical': 0.0, 'mean_word_length': 6.2444444444444445, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '269136', 'license': 'MIT', 'n_tokens_mistral': 124, 'n_tokens_neox': 120, 'n_words': 27, 'path': 'PyCaret/notebooks/01-Anatomy of Regression.ipynb', 'repo_name': 'hossainlab/ML', 'size': '325'}