Update pages/1player_information.py

pages/1player_information.py

@@ -26,13 +26,12 @@ if selected_player:
     player_data = df[df["Player"] == selected_player].iloc[0]
     labels = ["Test", "ODI", "T20", "IPL"]
     
-    # **Batting Stats Section**
     if show_batting:
-        st.subheader(f"Batting Statistics - {selected_player}")
-        col1, col2 = st.columns(2)
+        st.subheader(f"Batting Stats for {selected_player}")
         
+        col1, col2 = st.columns(2)
         with col1:
-            # Pie Chart - Matches Played Across Formats
+            # Pie Chart - Matches Played
             matches = [
                 player_data.get("Matches_Test", 0),
                 player_data.get("Matches_ODI", 0),
@@ -57,102 +56,25 @@ if selected_player:
             ax.set_ylabel("Runs Scored")
             ax.set_title(f"Runs Scored by {selected_player}")
             st.pyplot(fig)
-        
-        col3, col4 = st.columns(2)
-        
-        with col3:
-            # Bar Chart - 100s and 50s
-            hundreds = [
-                player_data.get("batting_100s_Test", 0),
-                player_data.get("batting_100s_ODI", 0),
-                player_data.get("batting_100s_T20", 0),
-                player_data.get("batting_100s_IPL", 0)
-            ]
-            fifties = [
-                player_data.get("batting_50s_Test", 0),
-                player_data.get("batting_50s_ODI", 0),
-                player_data.get("batting_50s_T20", 0),
-                player_data.get("batting_50s_IPL", 0)
-            ]
-            fig, ax = plt.subplots()
-            ax.bar(labels, hundreds, label="100s", color="gold")
-            ax.bar(labels, fifties, label="50s", color="blue", bottom=hundreds)
-            ax.set_ylabel("Count")
-            ax.set_title(f"Centuries & Fifties by {selected_player}")
-            ax.legend()
-            st.pyplot(fig)
-        
-        with col4:
-            # Line Chart - Strike Rate & Average
-            strike_rate = [
-                player_data.get("batting_SR_Test", 0),
-                player_data.get("batting_SR_ODI", 0),
-                player_data.get("batting_SR_T20", 0),
-                player_data.get("batting_SR_IPL", 0)
-            ]
-            batting_avg = [
-                player_data.get("batting_Average_Test", 0),
-                player_data.get("batting_Average_ODI", 0),
-                player_data.get("batting_Average_T20", 0),
-                player_data.get("batting_Average_IPL", 0)
-            ]
-            fig, ax = plt.subplots()
-            ax.plot(labels, strike_rate, marker='o', linestyle='-', color='red', label="Strike Rate")
-            ax.plot(labels, batting_avg, marker='s', linestyle='--', color='green', label="Batting Average")
-            ax.set_ylabel("Value")
-            ax.set_title(f"Strike Rate & Batting Average of {selected_player}")
-            ax.legend()
-            st.pyplot(fig)
 
-    # **Bowling Stats Section**
     if show_bowling:
-        st.subheader(f"Bowling Statistics - {selected_player}")
-        col1, col2 = st.columns(2)
+        st.subheader(f"Bowling Stats for {selected_player}")
 
+        col1, col2 = st.columns(2)
         with col1:
-            # Pie Chart - Wickets Taken Across Formats
+            # Pie Chart - Wickets Taken
             wickets = [
-                player_data.get("Wickets_Test", 0),
-                player_data.get("Wickets_ODI", 0),
-                player_data.get("Wickets_T20", 0),
-                player_data.get("Wickets_IPL", 0)
+                0 if pd.isna(player_data.get("bowling_Test_Avg", 0)) else float(player_data.get("bowling_Test_Avg", 0)),
+                0 if pd.isna(player_data.get("bowling_ODI_Wickets", 0)) else int(player_data.get("bowling_ODI_Wickets", 0)),
+                0 if pd.isna(player_data.get("bowling_T20_Wickets", 0)) else int(player_data.get("bowling_T20_Wickets", 0)),
+                0 if pd.isna(player_data.get("bowling_IPL_Wickets", 0)) else int(player_data.get("bowling_IPL_Wickets", 0))
             ]
-            fig, ax = plt.subplots(figsize=(5, 3))
+            fig, ax = plt.subplots()
             ax.pie(wickets, labels=labels, autopct="%1.1f%%", startangle=90)
             ax.set_title(f"Wickets Taken by {selected_player}")
             st.pyplot(fig)
 
         with col2:
-            # Bar Chart - Economy Rate
-            economy_rate = [
-                player_data.get("Economy_Test", 0),
-                player_data.get("Economy_ODI", 0),
-                player_data.get("Economy_T20", 0),
-                player_data.get("Economy_IPL", 0)
-            ]
-            fig, ax = plt.subplots(figsize=(5, 3))
-            ax.bar(labels, economy_rate, color=["gold", "green", "blue", "red"])
-            ax.set_ylabel("Economy Rate")
-            ax.set_title(f"Economy Rate of {selected_player}")
-            st.pyplot(fig)
-
-        col3, col4 = st.columns(2)
-
-        with col3:
-            # Bar Chart - Balls Bowled
-            balls_bowled = [
-                player_data.get("bowling_Balls_Test", 0),
-                player_data.get("bowling_Balls_ODI", 0),
-                player_data.get("bowling_Balls_T20", 0),
-                player_data.get("bowling_Balls_IPL", 0)
-            ]
-            fig, ax = plt.subplots(figsize=(5, 3))
-            ax.bar(labels, balls_bowled, color=["red", "green", "blue", "purple"])
-            ax.set_ylabel("Balls Bowled")
-            ax.set_title(f"Balls Bowled by {selected_player}")
-            st.pyplot(fig)
-
-        with col4:
             # Bar Chart - Maidens Bowled
             maidens_bowled = [
                 player_data.get("bowling_Maidens_Test", 0),