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New feature to filter datasets by column and its corresponding values #53

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New feature to filter datasets by column and its corresponding values #53

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9 changes: 9 additions & 0 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,15 @@ sd.compile(
full_validation=True, # Optional: to save time, leave the default False value. If True, analyze consistency on modalities between columns.
date_compile_auc="01/01/2022", # Optional: useful when computing the drift for a time that is not now
datadrift_file="datadrift_auc.csv", # Optional: name of the csv file that contains the performance history of data drift
filter_column="name", # Optional: Name of the column you wish to filter
filter_values=[
"France",
"Ottomans",
"Austria",
"Poland",
"Brandenburg",
"Bohemia",
], # Optional: Names of the values from the column you chose above that you wish to filter.
)
```

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6 changes: 6 additions & 0 deletions eurybia/core/smartdrift.py
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Expand Up @@ -198,6 +198,8 @@ def __init__(
def compile(
self,
full_validation=False,
filter_column=None,
filter_values=None,
ignore_cols: list = list(),
sampling=True,
sample_size=100000,
Expand Down Expand Up @@ -236,6 +238,10 @@ def compile(
>>> SD.compile()

"""
print("FILTERING")
if filter_column and filter_values:
self.df_current = self.df_current[self.df_current[filter_column].isin(filter_values)]
self.df_baseline = self.df_baseline[self.df_baseline[filter_column].isin(filter_values)]
if datadrift_file is not None:
self.datadrift_file = datadrift_file
if hyperparameter is not None:
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