Update app.py

app.py

@@ -0,0 +1,94 @@
+import streamlit as st
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+import plotly.express as px
+
+# Load the dataset
+df = pd.read_csv("cric_final.csv")
+
+st.title("🏏 Player Performance Dashboard")
+
+# ✅ Dropdown to Select Player
+selected_player = st.selectbox("Select a Player", df["Player"].unique())
+
+# Get Player Data
+player_data = df[df["Player"] == selected_player]
+
+if not player_data.empty:
+    # Replace None/NaN with "-" only in batting and bowling columns
+    batting_cols = [col for col in df.columns if "batting" in col.lower()]
+    bowling_cols = [col for col in df.columns if "bowling" in col.lower()]
+
+    player_data[batting_cols] = player_data[batting_cols].fillna("-")
+    player_data[bowling_cols] = player_data[bowling_cols].fillna("-")
+
+    # ✅ Only 2 Tabs now: Batting and Bowling
+    tab1, tab2 = st.tabs(["📈 Batting Performance", "🎯 Bowling Performance"])
+
+    with tab1:
+        st.write("### 📊 Batting Performance")
+
+        # Bar Chart for Batting Runs
+        fig, ax = plt.subplots(figsize=(7, 5))
+        sns.barplot(
+            x=["Test", "ODI", "T20", "IPL"],
+            y=player_data.iloc[0][["batting_Runs_Test", "batting_Runs_ODI", "batting_Runs_T20", "batting_Runs_IPL"]],
+            palette="magma",
+            ax=ax
+        )
+        ax.set_ylabel("Total Runs", fontsize=14)
+        ax.set_title(f"Batting Performance of {selected_player}", fontsize=16)
+        ax.grid(True, axis='y', linestyle='--', alpha=0.7)
+        st.pyplot(fig)
+
+        # Half-Centuries (50s) vs Centuries (100s)
+        st.write("### Half-Centuries (50s) vs Centuries (100s)")
+        fig, ax = plt.subplots(figsize=(7, 5))
+        x_labels = ["Test", "ODI", "T20", "IPL"]
+        x = range(len(x_labels))
+        fifties = player_data.iloc[0][["batting_50s_Test", "batting_50s_ODI", "batting_50s_T20", "batting_50s_IPL"]]
+        hundreds = player_data.iloc[0][["batting_100s_Test", "batting_100s_ODI", "batting_100s_T20", "batting_100s_IPL"]]
+
+        width = 0.4
+        ax.bar([i - width/2 for i in x], fifties, width=width, label="50s", color="skyblue")
+        ax.bar([i + width/2 for i in x], hundreds, width=width, label="100s", color="orange")
+
+        ax.set_xticks(x)
+        ax.set_xticklabels(x_labels)
+        ax.set_ylabel("Count", fontsize=14)
+        ax.set_title(f"50s vs 100s of {selected_player}", fontsize=16)
+        ax.legend()
+        ax.grid(axis="y", linestyle="--", alpha=0.7)
+        st.pyplot(fig)
+
+        # Pie Chart for Batting Runs Distribution
+        st.write("### Batting Runs Distribution")
+        runs = player_data.iloc[0][["batting_Runs_Test", "batting_Runs_ODI", "batting_Runs_T20", "batting_Runs_IPL"]]
+        fig_pie = px.pie(values=runs, names=x_labels, title="Batting Runs Distribution")
+        st.plotly_chart(fig_pie)
+
+    with tab2:
+        st.write("### 🎯 Bowling Performance")
+
+        # Bar Chart for Bowling Wickets
+        fig, ax = plt.subplots(figsize=(7, 5))
+        sns.barplot(
+            x=["Test", "ODI", "T20", "IPL"],
+            y=player_data.iloc[0][["bowling_Test_Wickets", "bowling_ODI_Wickets", "bowling_T20_Wickets", "bowling_IPL_Wickets"]],
+            palette="coolwarm",
+            ax=ax
+        )
+        ax.set_ylabel("Total Wickets", fontsize=14)
+        ax.set_title(f"Bowling Performance of {selected_player}", fontsize=16)
+        ax.grid(True, axis='y', linestyle='--', alpha=0.7)
+        st.pyplot(fig)
+
+        # Pie Chart for Bowling Wickets Distribution
+        st.write("### Bowling Wickets Distribution")
+        wickets = player_data.iloc[0][["bowling_Test_Wickets", "bowling_ODI_Wickets", "bowling_T20_Wickets", "bowling_IPL_Wickets"]]
+        fig_pie_bowl = px.pie(values=wickets, names=x_labels, title="Bowling Wickets Distribution")
+        st.plotly_chart(fig_pie_bowl)
+
+else:
+    st.warning("⚠️ Player not found in the dataset.")