<jupyter_start><jupyter_text><jupyter_code>!git clone https://github.com/sharad28/Tensile_-_compressive_strength.git
# !pip install pandas_profiling
import pandas as pd
from pandas_profiling import ProfileReport
import os
df = pd.read_csv('sharad28/Tensile_-_compressive_strength/artifacts/EDA_prepared_data/KNN_df.csv')
df.head()
df.shape
!pip install pandas-profiling==2.7.1
profile = ProfileReport(df)
# profile = ProfileReport(df)

report_dir = '/content/Tensile_-_compressive_strength/artifacts/initial_prepared_data/REPORT'
rep_dir = os.path.join(report_dir,"before_missing_val_handling.html" )
profile.to_file(rep_dir)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1083969465648855, 'fraction_numerical': 0.010687022900763359, 'mean_word_length': 8.371428571428572, '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': '475409', 'license': 'MIT', 'n_tokens_mistral': 252, 'n_tokens_neox': 233, 'n_words': 32, 'path': 'artifacts/Research_env/6. xgboostregression.ipynb', 'repo_name': 'sharad28/Tensile_-_compressive_strength', 'size': '655'}