<jupyter_start><jupyter_text>Analysying the stackoverflow data<jupyter_code>import pandas as pd
file_path = 'survey_results_public.csv'
df = pd.read_csv(file_path)
df.head()
df['Professional'].value_counts()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11814345991561181, 'fraction_numerical': 0.0, 'mean_word_length': 11.526315789473685, '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': '25867', 'license': 'MIT', 'n_tokens_mistral': 94, 'n_tokens_neox': 89, 'n_words': 13, 'path': 'stackoverflow_2017/.ipynb_checkpoints/analysis-checkpoint.ipynb', 'repo_name': 'shindegau95/DevAnalysis', 'size': '237'}