Fix Task Dashboard Top Score and Entry columns

And also show submission time at higher granularity in plot

server/src/dashboard/helpers.py

@@ -163,35 +163,6 @@ def get_data_metadata(data_id):
     return df, meta_features, numerical_features, nominal_features
 
 
-def get_highest_rank(df, leaderboard):
-    df.sort_values(by=["upload_time"], inplace=True)
-    scores = []
-    # highest_rank = {}
-    highest_score = {}
-
-    setup_ids = []
-
-    for index, row in df.iterrows():
-        users = list(highest_score.keys())
-        new_user = row["uploader_name"] not in users
-        if row["setup_id"] not in setup_ids or new_user:
-            setup_ids.append(row["setup_id"])
-            score = row["value"]
-            if new_user or (score not in scores):
-                scores.append(score)
-                scores.sort(reverse=True)
-                # rank = scores.index(score) + 1
-                if new_user or (highest_score[row["uploader_name"]] < score):
-                    # highest_rank[row['uploader_name']] = rank
-                    highest_score[row["uploader_name"]] = score
-                # if highest_rank[row['uploader_name']] > row['Rank']:
-                #   highest_rank[row['uploader_name']] = row['Rank']
-    # leaderboard['highest_rank'] = list(highest_rank.values())
-
-    leaderboard["Top Score"] = list(highest_score.values())
-    return leaderboard
-
-
 def splitDataFrameList(df, target_column):
     """df = dataframe to split,
     target_column = the column containing the values to split

server/src/dashboard/task_callbacks.py

@@ -127,6 +127,7 @@ def update_task_plots(pathname, metric, n_clicks):
                 ),
             )
         ]
+
         layout = go.Layout(
             autosize=False,
             margin={"l": 400},
@@ -158,7 +159,6 @@ def update_task_plots(pathname, metric, n_clicks):
             tick_text.append(link)
 
         df["upload_time"] = pd.to_datetime(df["upload_time"])
-        df["upload_time"] = df["upload_time"].dt.date
 
         data = [
             go.Scatter(
@@ -177,7 +177,7 @@ def update_task_plots(pathname, metric, n_clicks):
             )
         ]
         layout = go.Layout(
-            title="Contributions over time,<br>every point is a run, "
+            title="Contributions over time, every point is a run."
             "click for details",
             autosize=True,
             margin={"l": 100},
@@ -194,29 +194,13 @@ def update_task_plots(pathname, metric, n_clicks):
         fig1 = go.Figure(data, layout)
 
         # Leaderboard table
+        max_score_by_uploader = df[["uploader_name", "value"]].groupby(["uploader_name"]).max()
+        max_score_by_uploader = max_score_by_uploader.to_dict()["value"]
+        submissions_by_uploader = df["uploader_name"].value_counts().to_dict()
 
-        top_uploader = df.sort_values("value", ascending=False).groupby(
-            ["uploader_name"], sort=False
-        )
-        name = top_uploader["uploader_name"].unique()
-        rank = list(range(1, len(name) + 1))
-        entries = top_uploader["uploader_name"].value_counts().values
-        leaderboard = pd.DataFrame(
-            {"Rank": rank, "Name": name, "Entries": entries}
-        ).reset_index()
-        leaderboard.drop("Name", axis=1, inplace=True)
-        ranks = []
-        df = top_uploader.head(df.shape[1])
-        for uploader in df["uploader_name"]:
-            ranks.append(
-                leaderboard[leaderboard["uploader_name"] == uploader].Rank.values[0]
-            )
-        df["Rank"] = ranks
-
-        # Sort by time
-        df.sort_values(by=["upload_time"], inplace=True)
-        # Get highest score
-        leaderboard = get_highest_rank(df, leaderboard)
+        leaderboard = df.copy()[["uploader_name"]].drop_duplicates()
+        leaderboard["Entries"] = leaderboard["uploader_name"].apply(submissions_by_uploader.get)
+        leaderboard["Top Score"] = leaderboard["uploader_name"].apply(max_score_by_uploader.get)
 
         # Create table
         table = html.Div(