saving plots to subdirectories grouped by filter

This commit is contained in:
2026-01-28 15:58:38 +01:00
parent 365e70b834
commit 62e75fe899
3 changed files with 88 additions and 29 deletions

View File

@@ -39,7 +39,6 @@ def _():
def _(JPMCSurvey, QSF_FILE, RESULTS_FILE):
S = JPMCSurvey(RESULTS_FILE, QSF_FILE)
data_all = S.load_data()
data_all.collect()
return S, data_all
@@ -96,22 +95,9 @@ def _(mo):
@app.cell(hide_code=True)
def _(data_all, mo):
data_all_collected = data_all.collect()
age = mo.ui.multiselect(options=data_all_collected["QID1"], value=data_all_collected["QID1"].unique(), label="Select Age Group(s):")
income = mo.ui.multiselect(data_all_collected["QID15"], value=data_all_collected["QID15"], label="Select Income Group(s):")
gender = mo.ui.multiselect(data_all_collected["QID2"], value=data_all_collected["QID2"], label="Select Gender(s)")
ethnicity = mo.ui.multiselect(data_all_collected["QID3"], value=data_all_collected["QID3"], label="Select Ethnicities:")
consumer = mo.ui.multiselect(data_all_collected["Consumer"], value=data_all_collected["Consumer"], label="Select Consumer Groups:")
return age, consumer, ethnicity, gender, income
@app.cell
def _(age, consumer, ethnicity, gender, income, mo):
mo.md(f"""
# Data Filters
def _(S, mo):
filter_form = mo.md('''
# Data Filter
{age}
@@ -122,16 +108,26 @@ def _(age, consumer, ethnicity, gender, income, mo):
{income}
{consumer}
""")
return
'''
).batch(
age=mo.ui.multiselect(options=S.options_age, value=S.options_age, label="Select Age Group(s):"),
gender=mo.ui.multiselect(options=S.options_gender, value=S.options_gender, label="Select Gender(s):"),
ethnicity=mo.ui.multiselect(options=S.options_ethnicity, value=S.options_ethnicity, label="Select Ethnicities:"),
income=mo.ui.multiselect(options=S.options_income, value=S.options_income, label="Select Income Group(s):"),
consumer=mo.ui.multiselect(options=S.options_consumer, value=S.options_consumer, label="Select Consumer Groups:")
).form()
filter_form
return (filter_form,)
@app.cell
def _(S, age, consumer, data_all, ethnicity, gender, income):
data = S.filter_data(data_all, age=age.value, gender=gender.value, income=income.value, ethnicity=ethnicity.value, consumer=consumer.value)
def _(S, data_all, filter_form, mo):
_d = S.filter_data(data_all, age=filter_form.value['age'], gender=filter_form.value['gender'], income=filter_form.value['income'], ethnicity=filter_form.value['ethnicity'], consumer=filter_form.value['consumer'])
# Stop execution and prevent other cells from running if no data is selected
mo.stop(len(_d.collect()) == 0, mo.md("**No Data available for current filter combination**"))
data = _d
data.collect()
return (data,)

View File

@@ -24,10 +24,66 @@ class JPMCPlotsMixin:
# Lowercase and limit length
return clean.lower()[:100]
def _get_filter_slug(self) -> str:
"""Generate a directory-friendly slug based on active filters."""
parts = []
# Mapping of attribute name to (short_code, value, options_attr)
filters = [
('age', 'Age', getattr(self, 'filter_age', None), 'options_age'),
('gender', 'Gen', getattr(self, 'filter_gender', None), 'options_gender'),
('consumer', 'Cons', getattr(self, 'filter_consumer', None), 'options_consumer'),
('ethnicity', 'Eth', getattr(self, 'filter_ethnicity', None), 'options_ethnicity'),
('income', 'Inc', getattr(self, 'filter_income', None), 'options_income'),
]
for _, short_code, value, options_attr in filters:
if value is None:
continue
# Ensure value is a list for uniform handling
if not isinstance(value, list):
value = [value]
if len(value) == 0:
continue
# Check if all options are selected (equivalent to no filter)
# We compare the set of selected values to the set of all available options
master_list = getattr(self, options_attr, None)
if master_list and set(value) == set(master_list):
continue
if len(value) > 3:
# If more than 3 options selected, use count to keep slug short
val_str = f"{len(value)}_grps"
else:
# Join values with '+'
clean_values = []
for v in value:
# Simple sanitization: keep alphanum and hyphens/dots, remove others
s = str(v)
# Remove special chars that might be problematic in dir names
s = re.sub(r'[^\w\-\.]', '', s)
clean_values.append(s)
val_str = "+".join(clean_values)
parts.append(f"{short_code}-{val_str}")
if not parts:
return "All_Respondents"
return "_".join(parts)
def _save_plot(self, fig: go.Figure, title: str) -> None:
"""Save plot to PNG file if fig_save_dir is set."""
if hasattr(self, 'fig_save_dir') and self.fig_save_dir:
path = Path(self.fig_save_dir)
# Add filter slug subfolder
filter_slug = self._get_filter_slug()
path = path / filter_slug
if not path.exists():
path.mkdir(parents=True, exist_ok=True)

View File

@@ -210,6 +210,13 @@ class JPMCSurvey(JPMCPlotsMixin):
# Rename columns with the extracted ImportIds
df.columns = new_columns
# Store unique values for filters (ignoring nulls) to detect "all selected" state
self.options_age = sorted(df['QID1'].drop_nulls().unique().to_list()) if 'QID1' in df.columns else []
self.options_gender = sorted(df['QID2'].drop_nulls().unique().to_list()) if 'QID2' in df.columns else []
self.options_consumer = sorted(df['Consumer'].drop_nulls().unique().to_list()) if 'Consumer' in df.columns else []
self.options_ethnicity = sorted(df['QID3'].drop_nulls().unique().to_list()) if 'QID3' in df.columns else []
self.options_income = sorted(df['QID15'].drop_nulls().unique().to_list()) if 'QID15' in df.columns else []
return df.lazy()
def _get_subset(self, q: pl.LazyFrame, QIDs, rename_cols=True, include_record_id=True) -> pl.LazyFrame:
@@ -239,24 +246,24 @@ class JPMCSurvey(JPMCPlotsMixin):
"""
# Apply filters
if age is not None:
self.filter_age = age
if age is not None:
q = q.filter(pl.col('QID1').is_in(age))
if gender is not None:
self.filter_gender = gender
if gender is not None:
q = q.filter(pl.col('QID2').is_in(gender))
if consumer is not None:
self.filter_consumer = consumer
if consumer is not None:
q = q.filter(pl.col('Consumer').is_in(consumer))
if ethnicity is not None:
self.filter_ethnicity = ethnicity
if ethnicity is not None:
q = q.filter(pl.col('QID3').is_in(ethnicity))
if income is not None:
self.filter_income = income
if income is not None:
q = q.filter(pl.col('QID15').is_in(income))
self.data_filtered = q