<jupyter_start><jupyter_text>Imports<jupyter_code>import os<jupyter_output><empty_output><jupyter_text>Functions<jupyter_code>def download_data(competition_name):
    !kaggle competitions download -o -p data {competition_name}
def get_competition_name():
    return os.getcwd().split(os.sep)[-1]<jupyter_output><empty_output><jupyter_text>Main<jupyter_code>download_data(get_competition_name())<jupyter_output>Downloading data_description.txt to data

Downloading train.csv.gz to data

Downloading train.csv to data

Downloading test.csv.gz to data

Downloading test.csv to data

Downloading sample_submission.csv.gz to data

Downloading sample_submission.csv to data
{'fraction_non_alphanumeric': 0.08845577211394302, 'fraction_numerical': 0.0014992503748125937, 'mean_word_length': 8.408450704225352, 'pattern_counts': {'":': 0, '<': 12, '<?xml version=': 0, '>': 12, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 10, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '252062', 'license': 'MIT', 'n_tokens_mistral': 234, 'n_tokens_neox': 232, 'n_words': 41, 'path': 'house-prices-advanced-regression-techniques/data_downloader.ipynb', 'repo_name': 'shrinivas93/kaggle', 'size': '667'}