Update app.py

app.py

@@ -1,77 +1,23 @@
 import streamlit as st
-import pandas as pd
-import plotly.express as px
-import plotly.graph_objects as go
 
-# Streamlit App Title
-st.title("🏏 Cricket Data Analysis 📊")
-
-# Load CSV Files using Streamlit Cache
-@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")
-
-# Load Data
-try:
-    batting_df = load_batting_data()
-    bowling_df = load_bowling_data()
-except FileNotFoundError as e:
-    st.error(f"❌ File not found: {e}")
-    st.stop()
-
-# Main Page Filters
-selected_country = st.selectbox("Select Country", sorted(batting_df["Country"].unique()))
-option = st.selectbox("Choose the Player", sorted(batting_df[batting_df["Country"] == selected_country]["player_name"].unique()))
-selected_format = st.selectbox("Select Format", ["All"] + list(batting_df["Format"].unique()) + ["IPL"])
-
-st.write("You selected:", option)
-
-# Filter Data
-filtered_batting_df = batting_df[(batting_df["player_name"] == option) & (batting_df["Country"] == selected_country)]
-filtered_bowling_df = bowling_df[(bowling_df["player_name"] == option) & (bowling_df["Country"] == selected_country)]
-
-if selected_format != "All":
-    filtered_batting_df = filtered_batting_df[filtered_batting_df["Format"] == selected_format]
-    filtered_bowling_df = filtered_bowling_df[filtered_bowling_df["Format"] == selected_format]
-
-# Convert NaN values to zero
-filtered_batting_df = filtered_batting_df.fillna(0)
-filtered_bowling_df = filtered_bowling_df.fillna(0)
-
-# Drop Unnecessary Columns
-display_batting_df = filtered_batting_df.drop(columns=["player_name", "Country"]).reset_index(drop=True)
-display_bowling_df = filtered_bowling_df.drop(columns=["player_name", "Country"]).reset_index(drop=True)
-
-# Display Raw Data
-st.subheader(f"🏏 Batting Stats - {option}")
-st.dataframe(display_batting_df)
-
-st.subheader(f"🎯 Bowling Stats - {option}")
-st.dataframe(display_bowling_df)
-
-# Batting Efficiency
-filtered_batting_df["Balls per Four"] = filtered_batting_df["Balls"] / filtered_batting_df["Fours"]
-filtered_batting_df["Balls per Six"] = filtered_batting_df["Balls"] / filtered_batting_df["Sixes"]
-
-# Bowling Efficiency
-filtered_bowling_df["Balls per Wicket"] = filtered_bowling_df["Balls"] / filtered_bowling_df["Wickets"]
-
-# Batting Visualizations
-st.subheader(f"🏏 Boundary Efficiency - {option}")
-fig = px.bar(filtered_batting_df, x="Format", y="Balls per Four", title="Balls Taken per Four Across Formats", color="Format")
-st.plotly_chart(fig)
-
-fig = px.bar(filtered_batting_df, x="Format", y="Balls per Six", title="Balls Taken per Six Across Formats", color="Format")
-st.plotly_chart(fig)
-
-# Bowling Visualizations
-st.subheader(f"🎯 Bowling Efficiency - {option}")
-fig = px.bar(filtered_bowling_df, x="Format", y="Eco", title="Bowling Economy Across Formats", color="Format")
-st.plotly_chart(fig)
-
-fig = px.bar(filtered_bowling_df, x="Format", y="Balls per Wicket", title="Balls Taken per Wicket Across Formats", color="Format")
-st.plotly_chart(fig)
+def set_background(image_url):
+    st.markdown(
+        f"""
+        <style>
+        .stApp {{
+            background: url({image_url});
+            background-size: cover;
+            background-position: center;
+            background-repeat: no-repeat;
+        }}
+        </style>
+        """,
+        unsafe_allow_html=True
+    )
+
+# Set background image
+image_url = "https://huggingface.co/spaces/Adityaganesh/Cricket_data/raw/main/istockphoto-177427917-612x612.jpg"
+set_background(image_url)
+
+st.title("Cricket Data Analysis")
+st.write("Now with a custom background image!")