Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+try:
+    clustered_data = pd.read_csv("clustered_data.csv")
+except FileNotFoundError:
+    print("Error: 'clustered_data.csv' not found. Make sure it's in the same directory.")
+    exit()
+
+players_2024 = sorted(clustered_data[clustered_data['year'] == 2024]['player_name'].unique())
+
+def get_similar_players(selected_player):
+    """Returns a table of similar players based on cluster, including selected player and year."""
+
+    if selected_player is None:
+        return pd.DataFrame(columns=['player_name', 'year', 'targets', 'receptions', 'rec_yards', 'air_yards', 'routes_ran', 'yprr', 'tprr', 'adot', 'target_share', 'year_two_half_ppr'])
+
+    try:
+        selected_player_data = clustered_data[clustered_data['player_name'] == selected_player].iloc[0].to_dict()
+        selected_player_cluster = selected_player_data['cluster']
+    except IndexError:
+        return pd.DataFrame(columns=['player_name', 'year', 'targets', 'receptions', 'rec_yards', 'air_yards', 'routes_ran', 'yprr', 'tprr', 'adot', 'target_share', 'year_two_half_ppr'])
+
+    similar_players = clustered_data[
+        (clustered_data['cluster'] == selected_player_cluster) & (clustered_data['player_name'] != selected_player)
+    ].copy()
+
+    # Select and return desired columns, including 'player_name' and 'year'
+    similar_players = similar_players[['player_name', 'year', 'targets', 'receptions', 'rec_yards', 'air_yards', 'routes_ran', 'yprr', 'tprr', 'adot', 'target_share', 'year_two_half_ppr']]
+
+    # Round specified columns to two decimal places
+    for col in ['yprr', 'tprr', 'adot', 'target_share', 'year_two_half_ppr']:
+        similar_players[col] = similar_players[col].round(2)
+
+    # --- Corrected handling of selected player data ---
+    selected_player_df = pd.DataFrame([selected_player_data])  # Create DataFrame from dictionary
+    selected_player_df = selected_player_df[['player_name', 'year', 'targets', 'receptions', 'rec_yards', 'air_yards', 'routes_ran', 'yprr', 'tprr', 'adot', 'target_share', 'year_two_half_ppr']]  # Order columns
+    for col in ['yprr', 'tprr', 'adot', 'target_share', 'year_two_half_ppr']:
+        selected_player_df[col] = selected_player_df[col].round(2)
+    similar_players = pd.concat([selected_player_df, similar_players], ignore_index=True)
+
+    return similar_players
+
+with gr.Blocks() as demo:
+    player_dropdown = gr.Dropdown(choices=players_2024, label="Select a 2024 Player")
+    output_table = gr.DataFrame(label="Similar Players")
+
+    player_dropdown.change(get_similar_players, inputs=player_dropdown, outputs=output_table)
+
+demo.launch(share = True)