Update app.py

app.py

@@ -408,151 +408,160 @@ def server(input, output, session):
                 player_name = batter_name_id[batter_id]
                 stats = [merged_dict[x]['stat_title'] for x in merged_dict.keys()]
 
-                # Calculate percentiles and values
-                percentiles = [int((1 - x) * 100) if merged_dict[stat]["percentile_flip"] else int(x * 100) for x, stat in zip(new_player_percentiles.select(merged_dict.keys()).to_numpy()[0], merged_dict.keys())]
-                percentiles = np.clip(percentiles, 1, 100)
-                values = [str(f'{x:{merged_dict[stat]["format"]}}').strip('%') for x, stat in zip(new_player_metrics.select(merged_dict.keys()).to_numpy()[0], merged_dict.keys())]
-
-                # Get team logo URL
-                try:
-                    logo_url = image_dict[team_dict[player_team_dict[batter_id]]]
-                except KeyError:
-                    logo_url = "https://a.espncdn.com/combiner/i?img=/i/teamlogos/leagues/500/mlb.png&w=500&h=500"
-
-                # Create a custom colormap
-                color_list = ['#3661AD', '#B4CFD1', '#D82129']
-                cmap = LinearSegmentedColormap.from_list("custom_cmap", color_list)
-                norm = Normalize(vmin=0.1, vmax=0.9)
-                norm_percentiles = norm(percentiles / 100)
-                colors = [cmap(p) for p in norm_percentiles]
-
-                # Figure setup
-                num_stats = len(stats)
-                bar_height = 4.5
-                spacing = 1
-                fig_height = (bar_height + spacing) * num_stats
-                fig = plt.figure(figsize=(12, 12))
-                gs = GridSpec(6, 5, height_ratios=[0.1, 1.5, 0.9, 0.9, 7.6, 0.1], width_ratios=[0.2, 1.5, 7, 1.5, 0.2])
 
-                # Define subplots
-                ax_title = fig.add_subplot(gs[1, 2])
-                ax_table = fig.add_subplot(gs[2, :])
-                ax_fv_table = fig.add_subplot(gs[3, :])
-                ax_fv_table.axis('off')
-                ax = fig.add_subplot(gs[4, :])
-                ax_logo = fig.add_subplot(gs[1, 3])
-
-                ax.set_xlim(-1, 99)
-                ax.set_ylim(-1, 99)
-                ax.set_aspect("equal")
-                ax.axis("off")
-
-                # Draw each bar
-                for i, (stat, percentile, value, color) in enumerate(zip(stats, percentiles, values, colors)):
-                    y = fig_height - (i + 1) * (bar_height + spacing)
-                    ax.add_patch(patches.Rectangle((0, y + bar_height / 4), 100, bar_height / 2, color="#C7DCDC", lw=0))
-                    ax.add_patch(patches.Rectangle((0, y), percentile, bar_height, color=color, lw=0))
-                    circle_y = y + bar_height - bar_height / 2
-                    circle = plt.Circle((percentile, circle_y), bar_height / 2, color=color, ec='white', lw=1.5, zorder=10)
-                    ax.add_patch(circle)
-                    fs = 14
-                    ax.text(percentile, circle_y, f"{percentile}", ha="center", va="center", fontsize=10, color='white', zorder=10, fontweight='bold')
-                    ax.text(-5, y + bar_height / 2, stat, ha="right", va="center", fontsize=fs)
-                    ax.text(115, y + bar_height / 2, str(value), ha="right", va="center", fontsize=fs, zorder=5)
-                    if i < len(stats) and i > 0:
-                        ax.hlines(y=y + bar_height + spacing / 2, color='#399098', linestyle=(0, (5, 5)), linewidth=1, xmin=-33, xmax=0)
-                        ax.hlines(y=y + bar_height + spacing / 2, color='#399098', linestyle=(0, (5, 5)), linewidth=1, xmin=100, xmax=115)
-
-                # Draw vertical lines for 10%, 50%, and 90% with labels
-                for x, label, align, color in zip([10, 50, 90], ["Poor", "Average", "Great"], ['center', 'center', 'center'], color_list):
-                    ax.axvline(x=x, ymin=0, ymax=1, color='#FFF', linestyle='-', lw=1, zorder=1, alpha=0.5)
-                    ax.text(x, fig_height + 4, label, ha=align, va='center', fontsize=12, fontweight='bold', color=color)
-                    triangle = patches.RegularPolygon((x, fig_height + 1), 3, radius=1, orientation=0, color=color, zorder=2)
-                    ax.add_patch(triangle)
-
-                # # Title
-                # ax_title.set_ylim(0, 1)
-                # ax_title.text(0.5, 0.5, f"{player_name} - {player_position_dict[batter_id]}\nPercentile Rankings - 2024 AAA", ha="center", va="center", fontsize=24)
-                # ax_title.axis("off")
-                player_bio(batter_id, ax=ax_title, sport_id=sport_id, year_input=year_input)
-
-                # Add team logo
-                #response = requests.get(logo_url)
-                if input.switch():
-                    response = requests.get(input.logo_select())
-                else:
-                    response = requests.get(logo_url)
-                img = Image.open(BytesIO(response.content))
-                ax_logo.imshow(img)
-                ax_logo.axis("off")
-                ax.axis('equal')
-
-                # Metrics data table
-                metrics_data = {
-                    "Pitches": new_player_metrics['pitches'][0],
-                    "PA": new_player_metrics['pa'][0],
-                    "BIP": new_player_metrics['bip'][0],
-                    "HR": f"{new_player_metrics['home_run'][0]:.0f}",
-                    "AVG": f"{new_player_metrics['avg'][0]:.3f}",
-                    "OBP": f"{new_player_metrics['obp'][0]:.3f}",
-                    "SLG": f"{new_player_metrics['slg'][0]:.3f}",
-                    "OPS": f"{new_player_metrics['obp'][0] + new_player_metrics['slg'][0]:.3f}",
-                }
-                df_table = pd.DataFrame(metrics_data, index=[0])
-                ax_table.axis('off')
-                table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
-                for key, cell in table.get_celld().items():
-                    if key[0] == 0:
-                        cell.set_text_props(fontweight='bold')
-                table.auto_set_font_size(False)
-                table.set_fontsize(12)
-                table.scale(1, 1.5)
-
-                # Additional subplots for spacing
-                ax_top = fig.add_subplot(gs[0, :])
-                ax_bot = fig.add_subplot(gs[-1, :])
-                ax_top.axis('off')
-                ax_bot.axis('off')
-                ax_bot.text(0.05, 2, "By: Thomas Nestico (@TJStats)", ha="left", va="center", fontsize=14)
-                ax_bot.text(0.95, 2, "Data: MLB, Fangraphs", ha="right", va="center", fontsize=14)
-                fig.subplots_adjust(left=0.01, right=0.99, top=0.99, bottom=0.01)
+                
 
-                # Player headshot
-                ax_headshot = fig.add_subplot(gs[1, 1])
                 try:
-                    url = f'https://img.mlbstatic.com/mlb-photos/image/upload/c_fill,g_auto/w_640/v1/people/{batter_id}/headshot/milb/current.png'
-                    response = requests.get(url)
+                
+                    # Calculate percentiles and values
+                    percentiles = [int((1 - x) * 100) if merged_dict[stat]["percentile_flip"] else int(x * 100) for x, stat in zip(new_player_percentiles.select(merged_dict.keys()).to_numpy()[0], merged_dict.keys())]
+                    percentiles = np.clip(percentiles, 1, 100)
+                    values = [str(f'{x:{merged_dict[stat]["format"]}}').strip('%') for x, stat in zip(new_player_metrics.select(merged_dict.keys()).to_numpy()[0], merged_dict.keys())]
+    
+                    # Get team logo URL
+                    try:
+                        logo_url = image_dict[team_dict[player_team_dict[batter_id]]]
+                    except KeyError:
+                        logo_url = "https://a.espncdn.com/combiner/i?img=/i/teamlogos/leagues/500/mlb.png&w=500&h=500"
+    
+                    # Create a custom colormap
+                    color_list = ['#3661AD', '#B4CFD1', '#D82129']
+                    cmap = LinearSegmentedColormap.from_list("custom_cmap", color_list)
+                    norm = Normalize(vmin=0.1, vmax=0.9)
+                    norm_percentiles = norm(percentiles / 100)
+                    colors = [cmap(p) for p in norm_percentiles]
+    
+                    # Figure setup
+                    num_stats = len(stats)
+                    bar_height = 4.5
+                    spacing = 1
+                    fig_height = (bar_height + spacing) * num_stats
+                    fig = plt.figure(figsize=(12, 12))
+                    gs = GridSpec(6, 5, height_ratios=[0.1, 1.5, 0.9, 0.9, 7.6, 0.1], width_ratios=[0.2, 1.5, 7, 1.5, 0.2])
+    
+                    # Define subplots
+                    ax_title = fig.add_subplot(gs[1, 2])
+                    ax_table = fig.add_subplot(gs[2, :])
+                    ax_fv_table = fig.add_subplot(gs[3, :])
+                    ax_fv_table.axis('off')
+                    ax = fig.add_subplot(gs[4, :])
+                    ax_logo = fig.add_subplot(gs[1, 3])
+    
+                    ax.set_xlim(-1, 99)
+                    ax.set_ylim(-1, 99)
+                    ax.set_aspect("equal")
+                    ax.axis("off")
+    
+                    # Draw each bar
+                    for i, (stat, percentile, value, color) in enumerate(zip(stats, percentiles, values, colors)):
+                        y = fig_height - (i + 1) * (bar_height + spacing)
+                        ax.add_patch(patches.Rectangle((0, y + bar_height / 4), 100, bar_height / 2, color="#C7DCDC", lw=0))
+                        ax.add_patch(patches.Rectangle((0, y), percentile, bar_height, color=color, lw=0))
+                        circle_y = y + bar_height - bar_height / 2
+                        circle = plt.Circle((percentile, circle_y), bar_height / 2, color=color, ec='white', lw=1.5, zorder=10)
+                        ax.add_patch(circle)
+                        fs = 14
+                        ax.text(percentile, circle_y, f"{percentile}", ha="center", va="center", fontsize=10, color='white', zorder=10, fontweight='bold')
+                        ax.text(-5, y + bar_height / 2, stat, ha="right", va="center", fontsize=fs)
+                        ax.text(115, y + bar_height / 2, str(value), ha="right", va="center", fontsize=fs, zorder=5)
+                        if i < len(stats) and i > 0:
+                            ax.hlines(y=y + bar_height + spacing / 2, color='#399098', linestyle=(0, (5, 5)), linewidth=1, xmin=-33, xmax=0)
+                            ax.hlines(y=y + bar_height + spacing / 2, color='#399098', linestyle=(0, (5, 5)), linewidth=1, xmin=100, xmax=115)
+    
+                    # Draw vertical lines for 10%, 50%, and 90% with labels
+                    for x, label, align, color in zip([10, 50, 90], ["Poor", "Average", "Great"], ['center', 'center', 'center'], color_list):
+                        ax.axvline(x=x, ymin=0, ymax=1, color='#FFF', linestyle='-', lw=1, zorder=1, alpha=0.5)
+                        ax.text(x, fig_height + 4, label, ha=align, va='center', fontsize=12, fontweight='bold', color=color)
+                        triangle = patches.RegularPolygon((x, fig_height + 1), 3, radius=1, orientation=0, color=color, zorder=2)
+                        ax.add_patch(triangle)
+    
+                    # # Title
+                    # ax_title.set_ylim(0, 1)
+                    # ax_title.text(0.5, 0.5, f"{player_name} - {player_position_dict[batter_id]}\nPercentile Rankings - 2024 AAA", ha="center", va="center", fontsize=24)
+                    # ax_title.axis("off")
+                    player_bio(batter_id, ax=ax_title, sport_id=sport_id, year_input=year_input)
+    
+                    # Add team logo
+                    #response = requests.get(logo_url)
+                    if input.switch():
+                        response = requests.get(input.logo_select())
+                    else:
+                        response = requests.get(logo_url)
                     img = Image.open(BytesIO(response.content))
-                    ax_headshot.set_xlim(0, 1)
-                    ax_headshot.set_ylim(0, 1)
-                    ax_headshot.imshow(img, extent=[1/6, 5/6, 0, 1], origin='upper')
-                except PIL.UnidentifiedImageError:
+                    ax_logo.imshow(img)
+                    ax_logo.axis("off")
+                    ax.axis('equal')
+    
+                    # Metrics data table
+                    metrics_data = {
+                        "Pitches": new_player_metrics['pitches'][0],
+                        "PA": new_player_metrics['pa'][0],
+                        "BIP": new_player_metrics['bip'][0],
+                        "HR": f"{new_player_metrics['home_run'][0]:.0f}",
+                        "AVG": f"{new_player_metrics['avg'][0]:.3f}",
+                        "OBP": f"{new_player_metrics['obp'][0]:.3f}",
+                        "SLG": f"{new_player_metrics['slg'][0]:.3f}",
+                        "OPS": f"{new_player_metrics['obp'][0] + new_player_metrics['slg'][0]:.3f}",
+                    }
+                    df_table = pd.DataFrame(metrics_data, index=[0])
+                    ax_table.axis('off')
+                    table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
+                    for key, cell in table.get_celld().items():
+                        if key[0] == 0:
+                            cell.set_text_props(fontweight='bold')
+                    table.auto_set_font_size(False)
+                    table.set_fontsize(12)
+                    table.scale(1, 1.5)
+    
+                    # Additional subplots for spacing
+                    ax_top = fig.add_subplot(gs[0, :])
+                    ax_bot = fig.add_subplot(gs[-1, :])
+                    ax_top.axis('off')
+                    ax_bot.axis('off')
+                    ax_bot.text(0.05, 2, "By: Thomas Nestico (@TJStats)", ha="left", va="center", fontsize=14)
+                    ax_bot.text(0.95, 2, "Data: MLB, Fangraphs", ha="right", va="center", fontsize=14)
+                    fig.subplots_adjust(left=0.01, right=0.99, top=0.99, bottom=0.01)
+    
+                    # Player headshot
+                    ax_headshot = fig.add_subplot(gs[1, 1])
+                    try:
+                        url = f'https://img.mlbstatic.com/mlb-photos/image/upload/c_fill,g_auto/w_640/v1/people/{batter_id}/headshot/milb/current.png'
+                        response = requests.get(url)
+                        img = Image.open(BytesIO(response.content))
+                        ax_headshot.set_xlim(0, 1)
+                        ax_headshot.set_ylim(0, 1)
+                        ax_headshot.imshow(img, extent=[1/6, 5/6, 0, 1], origin='upper')
+                    except PIL.UnidentifiedImageError:
+                        ax_headshot.axis('off')
+                        #return
                     ax_headshot.axis('off')
-                    #return
-                ax_headshot.axis('off')
-                ax_table.set_title('Season Summary', style='italic')
-
-                # Fangraphs scouting grades table
-                print(batter_id)
-                
-                if batter_id not in dict_mlb_fg.keys():
-                    ax_fv_table.text(x=0.5, y=0.5, s='No Scouting Data', style='italic', ha='center', va='center', fontsize=20, bbox=dict(facecolor='white', alpha=1, pad=10))
-                    return
-                df_fv_table = df_prospects[(df_prospects['minorMasterId'] == dict_mlb_fg[batter_id])][['cFV', 'Hit', 'Game', 'Raw', 'Spd', 'Fld']].reset_index(drop=True)
-                ax_fv_table.axis('off')
-                if df_fv_table.empty:
-                    ax_fv_table.text(x=0.5, y=0.5, s='No Scouting Data', style='italic', ha='center', va='center', fontsize=20, bbox=dict(facecolor='white', alpha=1, pad=10))
-                    return
-                df_fv_table.columns = ['FV', 'Hit', 'Game', 'Raw', 'Spd', 'Fld']
-                table_fv = ax_fv_table.table(cellText=df_fv_table.values, colLabels=df_fv_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
-                for key, cell in table_fv.get_celld().items():
-                    if key[0] == 0:
-                        cell.set_text_props(fontweight='bold')
-                table_fv.auto_set_font_size(False)
-                table_fv.set_fontsize(12)
-                table_fv.scale(1, 1.5)
-                ax_fv_table.set_title('Fangraphs Scouting Grades', style='italic')
+                    ax_table.set_title('Season Summary', style='italic')
+    
+                    # Fangraphs scouting grades table
+                    print(batter_id)
+                    
+                    if batter_id not in dict_mlb_fg.keys():
+                        ax_fv_table.text(x=0.5, y=0.5, s='No Scouting Data', style='italic', ha='center', va='center', fontsize=20, bbox=dict(facecolor='white', alpha=1, pad=10))
+                        return
+                    df_fv_table = df_prospects[(df_prospects['minorMasterId'] == dict_mlb_fg[batter_id])][['cFV', 'Hit', 'Game', 'Raw', 'Spd', 'Fld']].reset_index(drop=True)
+                    ax_fv_table.axis('off')
+                    if df_fv_table.empty:
+                        ax_fv_table.text(x=0.5, y=0.5, s='No Scouting Data', style='italic', ha='center', va='center', fontsize=20, bbox=dict(facecolor='white', alpha=1, pad=10))
+                        return
+                    df_fv_table.columns = ['FV', 'Hit', 'Game', 'Raw', 'Spd', 'Fld']
+                    table_fv = ax_fv_table.table(cellText=df_fv_table.values, colLabels=df_fv_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
+                    for key, cell in table_fv.get_celld().items():
+                        if key[0] == 0:
+                            cell.set_text_props(fontweight='bold')
+                    table_fv.auto_set_font_size(False)
+                    table_fv.set_fontsize(12)
+                    table_fv.scale(1, 1.5)
+                    ax_fv_table.set_title('Fangraphs Scouting Grades', style='italic')
 
+                except ValueError:
+                    fig = plt.figure(figsize=(26,26))
+                    fig.text(x=0.1,y=0.9,s='No Statcast Data For This Batter',fontsize=36,ha='left')
+                    return fig
 
 
                 #plt.show()