EDA Toolkit 0.0.11a2
Data Doctor Updates
1. new_col_name
logic for when scale_conversion==None
, but there are cutoffs to be applied to a new column, allowing such situations to go through so that the new column is created.
2. Fix for apply_as_new_col_to_df
logic
Updated the logic for generating the new column name when apply_as_new_col_to_df=True
. This ensures that the column name is correctly assigned based on the applied transformation or cutoff.
Original code:
# New column name options when apply_as_new_col_to_df == True
if apply_as_new_col_to_df == True and scale_conversion == None and apply_cutoff == True:
new_col_name = feature_name + "_" + 'w_cutoff'
elif apply_as_new_col_to_df == True and scale_conversion != None:
new_col_name = feature_name + "_" + scale_conversion
**Updated version**:
```python
# Default new column name in case no conditions are met
new_col_name = feature_name
# New column name options when apply_as_new_col_to_df == True
if apply_as_new_col_to_df:
if scale_conversion is None and apply_cutoff:
new_col_name = feature_name + "_w_cutoff"
elif scale_conversion is not None:
new_col_name = feature_name + "_" + scale_conversion
3. Custom ValueError
for missing conditions
Added a custom ValueError
to handle cases where the user sets apply_as_new_col_to_df=True
but does not specify either a scale_conversion
or enable apply_cutoff
. This provides clearer feedback to users and avoids unexpected behavior.
4. New error-handling block:
if apply_as_new_col_to_df:
if scale_conversion is None and not apply_cutoff:
raise ValueError(
"When applying a new column with `apply_as_new_col_to_df=True`, "
"you must specify either a `scale_conversion` or set `apply_cutoff=True`."
)
Overall Changes
- Corrected the logic for generating new column names when transformations or cutoffs are applied.
- Added a custom
ValueError
whenapply_as_new_col_to_df=True
but neither a validscale_conversion
norapply_cutoff=True
is specified. - Updated the docstring to reflect the new logic and error handling.