Update space
Browse files- src/populate.py +2 -2
src/populate.py
CHANGED
@@ -18,7 +18,7 @@ def get_model_leaderboard_df(results_path: str, requests_path: str="", cols: lis
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df = pd.DataFrame.from_records(all_data_json)
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df = df[benchmark_cols]
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print(df.head())
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if rank_col: # if there is one col in rank_col, sort by that column and remove NaN values
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df = df.dropna(subset=benchmark_cols)
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@@ -27,7 +27,7 @@ def get_model_leaderboard_df(results_path: str, requests_path: str="", cols: lis
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avg_rank = df.iloc[:, 1:].mean(axis=1) # we'll skip NaN, instrad of deleting the whole row
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df["Average Rank"] = avg_rank
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df = df.sort_values(by=["Average Rank"], ascending=True)
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# df = df.sort_values(by=[AutoEvalColumn.score.name], ascending=True)
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# df[AutoEvalColumn.rank.name] = df[AutoEvalColumn.score.name].rank(ascending=True, method="min")
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df = pd.DataFrame.from_records(all_data_json)
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df = df[benchmark_cols]
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# print(df.head())
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if rank_col: # if there is one col in rank_col, sort by that column and remove NaN values
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df = df.dropna(subset=benchmark_cols)
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avg_rank = df.iloc[:, 1:].mean(axis=1) # we'll skip NaN, instrad of deleting the whole row
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df["Average Rank"] = avg_rank
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df = df.sort_values(by=["Average Rank"], ascending=True)
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df = df.fillna('--')
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# df = df.sort_values(by=[AutoEvalColumn.score.name], ascending=True)
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# df[AutoEvalColumn.rank.name] = df[AutoEvalColumn.score.name].rank(ascending=True, method="min")
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