basic working tables

.gitignore

@@ -1,3 +1,7 @@
+#project
+main.ipynb
+.vscode/*
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

.python-version

@@ -0,0 +1 @@
+3.13

pyproject.toml

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+[project]
+name = "space-jam-dashboard"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "espn-api>=0.43.0",
+    "pandas>=2.2.3",
+    "panel>=1.5.4",
+]

src/backend.py

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+import pandas as pd
+
+from espn_api.basketball import League
+
+import constants as const
+
+
+def get_league(league_id: int = const.SPACEJAM_LEAGUE_ID, year: int = const.YEAR):
+    return League(league_id, year)
+
+
+def get_league_all_raw_stats_df(league: League):
+    league_stats = []
+    for team in league.teams:
+        temp_dict = team.stats.copy()
+        temp_dict["Team"] = team.team_name
+        temp_dict["Standing"] = team.standing
+        league_stats.append(temp_dict)
+
+    df = pd.DataFrame(league_stats)
+
+    df = df.astype(const.ALL_RAW_DATA_TABLE_DEF)
+    return df[list(const.ALL_RAW_DATA_TABLE_DEF.keys())]
+
+
+def get_league_all_raw_data_rankings(league: League):
+    raw_stats_df = get_league_all_raw_stats_df(league)
+    # Rank only numeric columns
+    want_big_num_df = raw_stats_df[const.WANT_BIG_NUM]
+    want_small_num_df = raw_stats_df[const.WANT_SMALL_NUM]
+    want_big_ranked_df = want_big_num_df.rank(ascending=False).astype(int)
+    want_small_ranked_df = want_small_num_df.rank(ascending=True).astype(int)
+    ranked_df = pd.concat([want_big_ranked_df, want_small_ranked_df], axis=1)
+    ranked_df["Avg. Cat. Rank"] = ranked_df.mean(axis=1)
+
+    # Concatenate with non-numeric columns
+    ranked_df = pd.concat(
+        [
+            ranked_df,
+            raw_stats_df.select_dtypes(exclude="number"),
+        ],
+        axis=1,
+    )
+
+    return ranked_df[list(const.ALL_DATA_RANKED_TABLE_DEF.keys())]
+
+
+def get_league_cat_raw_stats_df(league: League):
+    league_stats = []
+    for team in league.teams:
+        temp_dict = team.stats.copy()
+        temp_dict["Team"] = team.team_name
+        temp_dict["Standing"] = team.standing
+        league_stats.append(temp_dict)
+
+    df = pd.DataFrame(league_stats)
+
+    df = df.astype(const.CAT_ONLY_RAW_DATA_TABLE_DEF)
+    return df[list(const.CAT_ONLY_RAW_DATA_TABLE_DEF.keys())]
+
+
+def get_league_cat_data_rankings(league: League):
+    raw_stats_df = get_league_all_raw_stats_df(league)
+    # Rank only numeric columns
+    want_big_num_df = raw_stats_df[const.WANT_BIG_NUM]
+    want_small_num_df = raw_stats_df[const.WANT_SMALL_NUM]
+    want_big_ranked_df = want_big_num_df.rank(ascending=False).astype(int)
+    want_small_ranked_df = want_small_num_df.rank(ascending=True).astype(int)
+    ranked_df = pd.concat([want_big_ranked_df, want_small_ranked_df], axis=1)
+    ranked_df["Avg. Cat. Rank"] = ranked_df.mean(axis=1)
+
+    # Concatenate with non-numeric columns
+    ranked_df = pd.concat(
+        [
+            ranked_df,
+            raw_stats_df.select_dtypes(exclude="number"),
+        ],
+        axis=1,
+    )
+    return ranked_df[list(const.CAT_ONLY_DATA_RANKED_TABLE_DEF.keys())]
+
+
+if __name__ == "__main__":
+    pass

src/constants.py

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+SPACEJAM_LEAGUE_ID = 233677
+YEAR = 2025
+
+ALL_RAW_DATA_TABLE_DEF = {
+    "Team": str,
+    "Standing": int,
+    "PTS": int,
+    "BLK": int,
+    "STL": int,
+    "AST": int,
+    "REB": int,
+    "TO": int,
+    "FGM": int,
+    "FGA": int,
+    "FTM": int,
+    "FTA": int,
+    "3PM": int,
+    "FG%": float,
+    "FT%": float,
+}
+
+ALL_DATA_RANKED_TABLE_DEF = {
+    "Team": str,
+    "Standing": int,
+    "Avg. Cat. Rank": int,
+    "PTS": int,
+    "BLK": int,
+    "STL": int,
+    "AST": int,
+    "REB": int,
+    "TO": int,
+    "FGM": int,
+    "FGA": int,
+    "FTM": int,
+    "FTA": int,
+    "3PM": int,
+    "FG%": int,
+    "FT%": int,
+}
+
+CAT_ONLY_RAW_DATA_TABLE_DEF = {
+    "Team": str,
+    "Standing": int,
+    "PTS": int,
+    "BLK": int,
+    "STL": int,
+    "AST": int,
+    "REB": int,
+    "TO": int,
+    "3PM": int,
+    "FG%": float,
+    "FT%": float,
+}
+
+CAT_ONLY_DATA_RANKED_TABLE_DEF = {
+    "Team": str,
+    "Standing": int,
+    "Avg. Cat. Rank": int,
+    "PTS": int,
+    "BLK": int,
+    "STL": int,
+    "AST": int,
+    "REB": int,
+    "TO": int,
+    "3PM": int,
+    "FG%": int,
+    "FT%": int,
+}
+
+WANT_BIG_NUM = [
+    "PTS",
+    "BLK",
+    "STL",
+    "AST",
+    "REB",
+    "FGM",
+    "FGA",
+    "FTM",
+    "FTA",
+    "3PM",
+    "FG%",
+    "FT%",
+]
+
+WANT_SMALL_NUM = ["Standing", "TO"]

src/frontend.py

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+import panel as pn
+import backend as be
+
+pn.extension("tabulator")
+
+all_stats = be.get_league_all_raw_stats_df(be.get_league())
+all_rankings = be.get_league_all_raw_data_rankings(be.get_league())
+cat_stats = be.get_league_cat_raw_stats_df(be.get_league())
+cat_rankings = be.get_league_cat_data_rankings(be.get_league())
+
+
+def get_dataframe(mode: pn.widgets.Select):
+    if mode == "All Data - Raw Stats":
+        df = all_stats
+    elif mode == "All Data - Ranked":
+        df = all_rankings
+    elif mode == "Categories - Raw Stats":
+        df = cat_stats
+    elif mode == "Categories - Rankings":
+        df = cat_rankings
+    return df
+
+
+mode = pn.widgets.Select(
+    name="Mode",
+    options=[
+        "Categories - Rankings",
+        "Categories - Raw Stats",
+        "All Data - Ranked",
+        "All Data - Raw Stats",
+    ],
+)
+
+interactive_df = pn.bind(get_dataframe, mode)
+
+interactive_table = pn.widgets.Tabulator(interactive_df, theme="site", show_index=False)
+
+pn.template.ReactTemplate(
+    title="Space Jam Dashboard",
+    sidebar=[mode],
+    main=[interactive_table],
+    sidebar_width=150,
+).servable()