<jupyter_start><jupyter_text>Stratified dataset splitting Balance train and test set by:- classes frequency- commits- lines of code (retrieve this info)<jupyter_code>def prepare_dataset_bin(class_):
    for 
for class_ in columns:
    print("Preparing class", class_)<jupyter_output>Preparing class TooManyMethods
Preparing class ExcessiveMethodLength
Preparing class DataClass
Preparing class ExcessiveClassLength
Preparing class ExcessiveParameterList<jupyter_text>visualizing data<jupyter_code>plt.figure(figsize=(25,10))
dataset['TooManyMethods'].value_counts().plot(kind='bar',title='TooManyMethods')
plt.show()
dataset['ExcessiveClassLength'].value_counts().plot(kind='bar',title='ExcessiveClassLength')
plt.show()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.104, 'fraction_numerical': 0.005333333333333333, 'mean_word_length': 10.553846153846154, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 8, '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': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '142986', 'license': 'MIT', 'n_tokens_mistral': 246, 'n_tokens_neox': 225, 'n_words': 46, 'path': 'notebooks/Data_analysis.ipynb', 'repo_name': 'egmaziero/CodeSmells', 'size': '750'}