<jupyter_start><jupyter_text>Project progress<jupyter_code>progress_df = extract_project_progress_info(leadearboard,
                                            metric_colname='channel_{}'.format(PROJECT_METRIC),
                                            time_colname='finished')

project_progress(progress_df, width=600, heights=[50, 300])<jupyter_output><empty_output><jupyter_text>Experiments by person<jupyter_code>leadearboard[PROJECT_METRIC] = leadearboard['channel_{}'.format(PROJECT_METRIC)].astype(float)
person_stats = leadearboard.groupby('owner')['finished','running_time',PROJECT_METRIC].\
agg({'finished':'count','running_time':'sum',PROJECT_METRIC:'max'}).reset_index()
person_stats['running_time_hours'] = person_stats['running_time']/3600
person_stats<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1325, 'fraction_numerical': 0.015, 'mean_word_length': 5.73109243697479, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 4, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '140216', 'license': 'MIT', 'n_tokens_mistral': 265, 'n_tokens_neox': 248, 'n_words': 18, 'path': 'notebooks/3.0-project_progress.ipynb', 'repo_name': 'jakubczakon/credit-default-prediction', 'size': '800'}