def pivot_table(
df: pd.DataFrame,
form_data: Dict[str, Any],
datasource: Optional["BaseDatasource"] = None,
) -> pd.DataFrame:
"""
Pivot table (v1).
"""
verbose_map = datasource.data["verbose_map"] if datasource else None
if form_data.get("granularity") == "all" and DTTM_ALIAS in df:
del df[DTTM_ALIAS]
# v1 func names => v2 func names
func_map = {
"sum": "Sum",
"mean": "Average",
"min": "Minimum",
"max": "Maximum",
"std": "Sample Standard Deviation",
"var": "Sample Variance",
}
return pivot_df(
df,
rows=get_column_names(form_data.get("groupby"), verbose_map),
columns=get_column_names(form_data.get("columns"), verbose_map),
metrics=get_metric_names(form_data["metrics"], verbose_map),
aggfunc=func_map.get(form_data.get("pandas_aggfunc", "sum"), "Sum"),
transpose_pivot=bool(form_data.get("transpose_pivot")),
combine_metrics=bool(form_data.get("combine_metric")),
show_rows_total=bool(form_data.get("pivot_margins")),
show_columns_total=bool(form_data.get("pivot_margins")),
apply_metrics_on_rows=False,
)
def test_get_column_names():
assert get_column_names([STR_COLUMN, SQL_ADHOC_COLUMN]) == [
"my_column",
"My Adhoc Column",
]
assert get_column_names(
[STR_COLUMN, SQL_ADHOC_COLUMN],
{"my_column": "My Column"},
) == ["My Column", "My Adhoc Column"]
def pivot_table_v2(
df: pd.DataFrame,
form_data: Dict[str, Any],
datasource: Optional["BaseDatasource"] = None,
) -> pd.DataFrame:
"""
Pivot table v2.
"""
verbose_map = datasource.data["verbose_map"] if datasource else None
if form_data.get("granularity_sqla") == "all" and DTTM_ALIAS in df:
del df[DTTM_ALIAS]
return pivot_df(
df,
rows=get_column_names(form_data.get("groupbyRows"), verbose_map),
columns=get_column_names(form_data.get("groupbyColumns"), verbose_map),
metrics=get_metric_names(form_data["metrics"], verbose_map),
aggfunc=form_data.get("aggregateFunction", "Sum"),
transpose_pivot=bool(form_data.get("transposePivot")),
combine_metrics=bool(form_data.get("combineMetric")),
show_rows_total=bool(form_data.get("rowTotals")),
show_columns_total=bool(form_data.get("colTotals")),
apply_metrics_on_rows=form_data.get("metricsLayout") == "ROWS",
)
def column_names(self) -> List[str]:
"""Return column names (labels). Gives priority to groupbys if both groupbys
and metrics are non-empty, otherwise returns column labels."""
return get_column_names(self.columns)