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fix: fix included columns in contingnecy tables #145

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Sep 22, 2023
Merged

fix: fix included columns in contingnecy tables #145

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18 changes: 13 additions & 5 deletions edvart/report_sections/bivariate_analysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -813,16 +813,22 @@ def contingency_tables(
Data based on which to create a contingency table.
columns : List[str], optional
Which columns to generate pair-wise contingency tables for.
All columns which contain more than 1 unique value are used by default.
Columns which contain only null values are always excluded.
Columns with more than `table_threshold` unique values are excluded.
Columns which contain only null values are excluded.
To override the excluded columns, specify `columns_pairs`.
Ignored if `columns_x` and `columns_y` or `columns_pairs` is specified.
columns_x : List[str], optional
If specified, contingency tables are plotted for each pair
in the cartesian product of `columns_x` and `columns_y`.
Columns with more than `table_threshold` unique values are excluded.
Columns which contain only null values are excluded.
If `columns_x` is specified, then `columns_y` must also be specified.
Ignored if `columns_pairs` is specified.
columns_y : List[str], optional
If specified, contingency tables are plotted for each pair
in the cartesian product of `columns_x` and `columns_y`.
Columns with more than `table_threshold` unique values are excluded.
Columns which contain only null values are excluded.
If `columns_y` is specified, then `columns_x` must also be specified.
Ignored if `columns_pairs` is specified.
columns_pairs : List[Tuple[str, str]], optional
Expand All @@ -842,18 +848,20 @@ def include_column(col: str) -> bool:

if (columns_x is None) != (columns_y is None):
raise ValueError("Either both or neither of columns_x, columns_y must be specified.")
if columns is None:
columns = list(df.columns)
columns = [col for col in df.columns if include_column(col)]

if columns_pairs is None:
if columns_x is None:
if columns is None:
columns = [col for col in df.columns if include_column(col)]
columns_pairs = list(itertools.combinations(columns, 2))
else:
columns_pairs = [
(col_x, col_y)
for (col_x, col_y) in itertools.product(columns_x, columns_y)
# Filter out pairs of columns which contain the same column since
# they make no sense in a contingency table
if col_x != col_y
if col_x != col_y and include_column(col_x) and include_column(col_y)
]

for column1, column2 in columns_pairs:
Expand Down