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b825223
fix remove_outlier_replicates to dismiss NaN rows from response colum…
paulsonak Jan 29, 2026
bdf9c9e
Initial plan
Copilot Jan 29, 2026
ddfff6f
Update atomsci/ddm/utils/curate_data.py
paulsonak Jan 29, 2026
9a86133
Update atomsci/ddm/utils/curate_data.py
paulsonak Jan 29, 2026
c4e8005
Update docstring to document NaN removal in remove_outlier_replicates
Copilot Jan 29, 2026
c0c779a
Add empty value for last entry in pGP_MDCK CSV
paulsonak Jan 29, 2026
367cd94
Update expected number of removed rows in test
paulsonak Jan 29, 2026
9ec03bd
Update atomsci/ddm/utils/curate_data.py
paulsonak Jan 29, 2026
cfb744d
Merge pull request #422 from ATOMScience-org/paulsonak-patch-1
paulsonak Jan 29, 2026
8766aea
Merge pull request #421 from ATOMScience-org/copilot/sub-pr-420
paulsonak Jan 29, 2026
886dfba
Merge branch '1.8.0' into bug_remove_outlier_replicates
stewarthe6 Feb 17, 2026
5ff8f2a
Merge branch '1.8.0' into bug_remove_outlier_replicates
stewarthe6 Feb 19, 2026
5430543
Tests dropping nan values in the response column print statement in r…
stewarthe6 Feb 19, 2026
27afad0
refactor: merge coverage reports from all test jobs for codecov
stewarthe6 Feb 19, 2026
e6d2b62
Updated coverage-merge. The old version was expecting the wrong file …
stewarthe6 Feb 20, 2026
f51263c
Fixed an incorrectly indented block in pytest.yml
stewarthe6 Feb 23, 2026
830fd1f
Corrected the path for the coverage reports
stewarthe6 Feb 24, 2026
656567d
Added debug statement to look for coverage reports
stewarthe6 Feb 24, 2026
b005aaa
Updated coverage locations. I'm leaving in the debug statements to he…
stewarthe6 Feb 24, 2026
bed149a
Even though the path is correct, these files are not being uploaded b…
stewarthe6 Feb 24, 2026
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7 changes: 6 additions & 1 deletion atomsci/ddm/utils/curate_data.py
Original file line number Diff line number Diff line change
Expand Up @@ -522,7 +522,12 @@ def remove_outlier_replicates(df, response_col='pIC50', id_col='compound_id', ma
result_df (DataFrame): Filtered data frame with outlier replicates removed.

"""


prev_len = len(df)
df=df.dropna(subset=[response_col])
# log.info(f"Removed {prev_len - len(df)} rows with missing {response_col} values")
print(f"Removed {prev_len - len(df)} rows with missing {response_col} values")

fr_df = freq_table(df, id_col, min_freq=2)
rep_ids = fr_df[id_col].values.tolist()
has_rep_df = df[df[id_col].isin(rep_ids)]
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