<jupyter_start><jupyter_text>01. Analyze original dataset<jupyter_code># MOunting google drive
from google.colab import drive
drive.mount('/gdrive')
# IMPORTS
import pandas as pd
# to display all the columns of the dataframe in the notebook
pd.pandas.set_option('display.max_rows', None,'display.max_columns', None)

import numpy as np
# Download helper functions script
!wget https://raw.githubusercontent.com/mrdbourke/tensorflow-deep-learning/main/extras/helper_functions.py


FILE_PATH='/content/drive/MyDrive/datasets/cars/dataset.csv'
DIR_DATA='/content/drive/MyDrive/datasets/cars/'

# load dataset
df = pd.read_csv(FILE_PATH,delimiter=';')
df.head()<jupyter_output>/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2882: DtypeWarning: Columns (23) have mixed types.Specify dtype option on import or set low_memory=False.
  exec(code_obj, self.user_global_ns, self.user_ns)
{'fraction_non_alphanumeric': 0.11529933481152993, 'fraction_numerical': 0.011086474501108648, 'mean_word_length': 6.224, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 1, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '451011', 'license': 'MIT', 'n_tokens_mistral': 318, 'n_tokens_neox': 306, 'n_words': 64, 'path': '01_analyze_dataset.ipynb', 'repo_name': 'PeterPirog/2019-CS109B', 'size': '902'}