Create Player Comparision

pages/Player Comparision

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+import streamlit as st
+import pandas as pd
+import plotly.graph_objects as go
+
+# Title
+st.title("🤝 Cricket Player Comparison")
+
+# Load data with caching
+@st.cache_data
+def load_batting_data():
+    return pd.read_csv("Batting_10_Teams_Final.csv")
+
+@st.cache_data
+def load_bowling_data():
+    return pd.read_csv("Bowling_10_Teams_Final.csv")
+
+try:
+    batting_df = load_batting_data()
+    bowling_df = load_bowling_data()
+except FileNotFoundError as e:
+    st.error(f"File not found: {e}")
+    st.stop()
+
+# Player selectors
+player1 = st.selectbox("Select First Player", sorted(batting_df["player_name"].unique()), key="p1")
+player2 = st.selectbox("Select Second Player", sorted(batting_df["player_name"].unique()), key="p2")
+
+# Filter player data and fill NaNs
+bat1 = batting_df[batting_df["player_name"] == player1].fillna(0)
+bat2 = batting_df[batting_df["player_name"] == player2].fillna(0)
+
+bowl1 = bowling_df[bowling_df["player_name"] == player1].fillna(0)
+bowl2 = bowling_df[bowling_df["player_name"] == player2].fillna(0)
+
+# Define stats to compare
+batting_metrics = ["Runs", "Average", "SR", "Fours", "Sixes"]
+bowling_metrics = ["Wickets", "Eco", "Average", "SR"]
+
+# Calculate averages or zeros if no data
+def get_avg(df, cols):
+    if df.empty:
+        return pd.Series({col: 0 for col in cols})
+    return df[cols].mean()
+
+bat1_avg = get_avg(bat1, batting_metrics)
+bat2_avg = get_avg(bat2, batting_metrics)
+
+bowl1_avg = get_avg(bowl1, bowling_metrics)
+bowl2_avg = get_avg(bowl2, bowling_metrics)
+
+# Batting comparison plot
+st.subheader("🏏 Batting Stats Comparison")
+fig_bat = go.Figure()
+fig_bat.add_trace(go.Bar(x=batting_metrics, y=bat1_avg, name=player1))
+fig_bat.add_trace(go.Bar(x=batting_metrics, y=bat2_avg, name=player2))
+fig_bat.update_layout(barmode='group', yaxis_title='Value', title='Batting Metrics Comparison')
+st.plotly_chart(fig_bat)
+
+# Bowling comparison plot
+st.subheader("🎯 Bowling Stats Comparison")
+fig_bowl = go.Figure()
+fig_bowl.add_trace(go.Bar(x=bowling_metrics, y=bowl1_avg, name=player1))
+fig_bowl.add_trace(go.Bar(x=bowling_metrics, y=bowl2_avg, name=player2))
+fig_bowl.update_layout(barmode='group', yaxis_title='Value', title='Bowling Metrics Comparison')
+st.plotly_chart(fig_bowl)