renamed notebooks and added significance test
This commit is contained in:
@@ -14,6 +14,15 @@ import utils
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from speaking_styles import SPEAKING_STYLES
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# %% Fixed Variables
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# RESULTS_FILE = 'data/exports/2-4-26/JPMC_Chase Brand Personality_Quant Round 1_February 4, 2026_Labels.csv'
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RESULTS_FILE = 'data/exports/debug/JPMC_Chase Brand Personality_Quant Round 1_February 2, 2026_Labels.csv'
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QSF_FILE = 'data/exports/OneDrive_2026-01-21/Soft Launch Data/JPMC_Chase_Brand_Personality_Quant_Round_1.qsf'
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BEST_CHOSEN_CHARACTER = "the_coach"
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# %%
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# CLI argument parsing for batch automation
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# When run as script: python 03_quant_report.script.py --age '["18 to 21 years"]' --consumer '["Starter"]'
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@@ -45,12 +54,9 @@ def parse_cli_args():
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# Only parse if running as script (not in Jupyter/interactive)
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try:
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# Check if running in Jupyter by looking for ipykernel
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get_ipython() # noqa: F821
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get_ipython() # noqa: F821 # type: ignore
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# Return namespace with all filters set to None
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no_filters = {f: None for f in FILTER_CONFIG}
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# debugging age
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no_filters['age'] = FILTER_CONFIG['age']
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return argparse.Namespace(**no_filters, filter_name=None)
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except NameError:
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args = parser.parse_args()
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@@ -62,19 +68,7 @@ def parse_cli_args():
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cli_args = parse_cli_args()
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# %%
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# file_browser = mo.ui.file_browser(
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# initial_path="./data/exports", multiple=False, restrict_navigation=True, filetypes=[".csv"], label="Select 'Labels' File"
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# )
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# file_browser
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# # %%
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# mo.stop(file_browser.path(index=0) is None, mo.md("**⚠️ Please select a `_Labels.csv` file above to proceed**"))
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# RESULTS_FILE = Path(file_browser.path(index=0))
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RESULTS_FILE = 'data/exports/2-4-26/JPMC_Chase Brand Personality_Quant Round 1_February 4, 2026_Labels.csv'
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QSF_FILE = 'data/exports/OneDrive_2026-01-21/Soft Launch Data/JPMC_Chase_Brand_Personality_Quant_Round_1.qsf'
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# %%
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S = QualtricsSurvey(RESULTS_FILE, QSF_FILE)
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@@ -83,46 +77,15 @@ try:
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except NotImplementedError as e:
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mo.stop(True, mo.md(f"**⚠️ {str(e)}**"))
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# %%
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BEST_CHOSEN_CHARACTER = "the_coach"
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# # %%
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# filter_form = mo.md('''
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# %% Build filtered dataset based on CLI args
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# {age}
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# {gender}
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# {ethnicity}
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# {income}
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# {consumer}
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# '''
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# ).batch(
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# age=mo.ui.multiselect(options=S.options_age, value=S.options_age, label="Select Age Group(s):"),
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# gender=mo.ui.multiselect(options=S.options_gender, value=S.options_gender, label="Select Gender(s):"),
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# ethnicity=mo.ui.multiselect(options=S.options_ethnicity, value=S.options_ethnicity, label="Select Ethnicities:"),
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# income=mo.ui.multiselect(options=S.options_income, value=S.options_income, label="Select Income Group(s):"),
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# consumer=mo.ui.multiselect(options=S.options_consumer, value=S.options_consumer, label="Select Consumer Groups:")
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# ).form()
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# mo.md(f'''
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# ---
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# # Data Filter
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# {filter_form}
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# ''')
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# %%
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# mo.stop(filter_form.value is None, mo.md("**Please submit filter above to proceed**"))
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# CLI args: None means "no filter applied" - filter_data() will skip None filters
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# Build filter values dict dynamically from FILTER_CONFIG
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_active_filters = {filter_name: getattr(cli_args, filter_name) for filter_name in FILTER_CONFIG}
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# %%
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# %% Apply filters
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_d = S.filter_data(data_all, **_active_filters)
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# Write filter description file if filter-name is provided
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@@ -174,14 +137,10 @@ if cli_args.filter_name and S.fig_save_dir:
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_header += "-" * 80 + "\n"
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_summary_file.write_text(_header + _summary_line)
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# Stop execution and prevent other cells from running if no data is selected
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# mo.stop(len(_d.collect()) == 0, mo.md("**No Data available for current filter combination**"))
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# Save to logical variable name for further analysis
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data = _d
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# data = data_validated
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data.collect()
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# %%
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# %%
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128
XX_statistical_significance.script.py
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128
XX_statistical_significance.script.py
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@@ -0,0 +1,128 @@
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"""Extra statistical significance analyses for quant report."""
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# %% Imports
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from utils import QualtricsSurvey
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import polars as pl
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import argparse
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import json
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import re
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# %% Fixed Variables
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RESULTS_FILE = 'data/exports/2-4-26/JPMC_Chase Brand Personality_Quant Round 1_February 4, 2026_Labels.csv'
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QSF_FILE = 'data/exports/OneDrive_2026-01-21/Soft Launch Data/JPMC_Chase_Brand_Personality_Quant_Round_1.qsf'
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# %% CLI argument parsing for batch automation
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# When run as script: uv run XX_statistical_significance.script.py --age '["18
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# Central filter configuration - add new filters here only
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# Format: 'cli_arg_name': 'QualtricsSurvey.options_* attribute name'
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FILTER_CONFIG = {
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'age': 'options_age',
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'gender': 'options_gender',
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'ethnicity': 'options_ethnicity',
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'income': 'options_income',
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'consumer': 'options_consumer',
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'business_owner': 'options_business_owner',
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'ai_user': 'options_ai_user',
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'investable_assets': 'options_investable_assets',
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'industry': 'options_industry',
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}
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def parse_cli_args():
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parser = argparse.ArgumentParser(description='Generate quant report with optional filters')
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# Dynamically add filter arguments from config
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for filter_name in FILTER_CONFIG:
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parser.add_argument(f'--{filter_name}', type=str, default=None, help=f'JSON list of {filter_name} values')
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parser.add_argument('--filter-name', type=str, default=None, help='Name for this filter combination (used for .txt description file)')
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# Only parse if running as script (not in Jupyter/interactive)
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try:
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# Check if running in Jupyter by looking for ipykernel
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get_ipython() # noqa: F821 # type: ignore
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# Return namespace with all filters set to None
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no_filters = {f: None for f in FILTER_CONFIG}
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return argparse.Namespace(**no_filters, filter_name=None)
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except NameError:
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args = parser.parse_args()
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# Parse JSON strings to lists
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for filter_name in FILTER_CONFIG:
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val = getattr(args, filter_name)
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setattr(args, filter_name, json.loads(val) if val else None)
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return args
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cli_args = parse_cli_args()
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# %%
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S = QualtricsSurvey(RESULTS_FILE, QSF_FILE)
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data_all = S.load_data()
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# %% Build filtered dataset based on CLI args
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# CLI args: None means "no filter applied" - filter_data() will skip None filters
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# Build filter values dict dynamically from FILTER_CONFIG
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_active_filters = {filter_name: getattr(cli_args, filter_name) for filter_name in FILTER_CONFIG}
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_d = S.filter_data(data_all, **_active_filters)
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# Write filter description file if filter-name is provided
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if cli_args.filter_name and S.fig_save_dir:
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# Get the filter slug (e.g., "All_Respondents", "Cons-Starter", etc.)
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_filter_slug = S._get_filter_slug()
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_filter_slug_dir = S.fig_save_dir / _filter_slug
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_filter_slug_dir.mkdir(parents=True, exist_ok=True)
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# Build filter description
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_filter_desc_lines = [
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f"Filter: {cli_args.filter_name}",
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"",
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"Applied Filters:",
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]
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_short_desc_parts = []
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for filter_name, options_attr in FILTER_CONFIG.items():
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all_options = getattr(S, options_attr)
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values = _active_filters[filter_name]
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display_name = filter_name.replace('_', ' ').title()
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# None means no filter applied (same as "All")
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if values is not None and values != all_options:
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_short_desc_parts.append(f"{display_name}: {', '.join(values)}")
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_filter_desc_lines.append(f" {display_name}: {', '.join(values)}")
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else:
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_filter_desc_lines.append(f" {display_name}: All")
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# Write detailed description INSIDE the filter-slug directory
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# Sanitize filter name for filename usage (replace / and other chars)
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_safe_filter_name = re.sub(r'[^\w\s-]', '_', cli_args.filter_name)
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_filter_file = _filter_slug_dir / f"{_safe_filter_name}.txt"
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_filter_file.write_text('\n'.join(_filter_desc_lines))
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# Append to summary index file at figures/<export_date>/filter_index.txt
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_summary_file = S.fig_save_dir / "filter_index.txt"
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_short_desc = "; ".join(_short_desc_parts) if _short_desc_parts else "All Respondents"
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_summary_line = f"{_filter_slug} | {cli_args.filter_name} | {_short_desc}\n"
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# Append or create the summary file
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if _summary_file.exists():
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_existing = _summary_file.read_text()
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# Avoid duplicate entries for same slug
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if _filter_slug not in _existing:
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with _summary_file.open('a') as f:
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f.write(_summary_line)
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else:
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_header = "Filter Index\n" + "=" * 80 + "\n\n"
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_header += "Directory | Filter Name | Description\n"
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_header += "-" * 80 + "\n"
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_summary_file.write_text(_header + _summary_line)
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# Save to logical variable name for further analysis
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data = _d
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data.collect()
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# %%
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