Update pages/1player_information.py

pages/1player_information.py

@@ -3,17 +3,46 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 
+# Set page configuration
+st.set_page_config(page_title="Cricket Legends: Career Insights & Visualizations", layout="wide")
+
+# Cricket-Themed Background
+page_bg = """
+<style>
+    [data-testid="stAppViewContainer"] {
+        background: url("https://wallpapercave.com/wp/wp7418478.jpg");
+        background-size: cover;
+    }
+    [data-testid="stHeader"] {
+        background: rgba(0,0,0,0);
+    }
+    [data-testid="stSidebar"] {
+        background: rgba(0,0,0,0.9);
+    }
+    h1, h2, h3, h4, h5, h6 {
+        color: white !important;
+    }
+    .stTextInput>div>div>input {
+        background-color: #f5f5f5;
+        color: black;
+    }
+</style>
+"""
+st.markdown(page_bg, unsafe_allow_html=True)
+
+# App Title
+st.title("🏏 Cricket Legends: Career Insights & Visualizations")
+
 # Load data
-file_path = "Final.csv"
+file_path = "Final.csv"  # Ensure this file exists in your working directory
 df = pd.read_csv(file_path)
 
-st.title("South Africa Cricket Players - Career Visualizations")
-
 # Enter Player Name
 player_input = st.text_input("Enter Player Name:")
 
 if player_input:
     selected_player = player_input.strip()
+    
     if selected_player in df["Player"].values:
         player_data = df[df["Player"] == selected_player].iloc[0]
 
@@ -25,9 +54,11 @@ if player_input:
             player_data["Matches_IPL"]
         ]
         labels = ["Test", "ODI", "T20", "IPL"]
+        
         fig, ax = plt.subplots()
-        ax.pie(matches, labels=labels, autopct="%1.1f%%", startangle=90, colors=["blue", "green", "red", "purple"])
-        ax.set_title(f"Matches Played by {selected_player}")
+        ax.pie(matches, labels=labels, autopct="%1.1f%%", startangle=90, 
+               colors=["#6495ED", "#3CB371", "#FF6347", "#9370DB"])
+        ax.set_title(f"Matches Played by {selected_player}", fontsize=14)
         st.pyplot(fig)
 
         # Bar Chart - Runs Scored in Different Formats
@@ -38,17 +69,17 @@ if player_input:
             player_data["batting_Runs_IPL"]
         ]
         fig, ax = plt.subplots()
-        ax.bar(labels, batting_runs, color=["blue", "green", "red", "purple"])
-        ax.set_ylabel("Runs Scored")
-        ax.set_title(f"Runs Scored by {selected_player}")
+        ax.bar(labels, batting_runs, color=["#FFD700", "#008000", "#1E90FF", "#FF4500"])
+        ax.set_ylabel("Runs Scored", fontsize=12)
+        ax.set_title(f"Runs Scored by {selected_player}", fontsize=14)
         st.pyplot(fig)
 
-        # Scatter Plot - Matches vs Runs
+        # Scatter Plot - Matches vs Runs (ODIs)
         fig, ax = plt.subplots()
-        sns.scatterplot(x=df["Matches_ODI"], y=df["batting_Runs_ODI"], ax=ax)
-        ax.set_xlabel("Matches Played")
-        ax.set_ylabel("Runs Scored")
-        ax.set_title("Matches vs Runs in ODIs (All Players)")
+        sns.scatterplot(x=df["Matches_ODI"], y=df["batting_Runs_ODI"], ax=ax, color="#1E90FF", edgecolor='black')
+        ax.set_xlabel("Matches Played", fontsize=12)
+        ax.set_ylabel("Runs Scored", fontsize=12)
+        ax.set_title("Matches vs Runs in ODIs (All Players)", fontsize=14)
         st.pyplot(fig)
 
         # Line Chart - Batting Average Over Formats
@@ -59,18 +90,18 @@ if player_input:
             player_data["batting_Runs_IPL"] / max(1, player_data["batting_Innings_IPL"])
         ]
         fig, ax = plt.subplots()
-        ax.plot(labels, batting_average, marker='o', linestyle='-', color='orange')
-        ax.set_ylabel("Batting Average")
-        ax.set_title(f"Batting Average of {selected_player}")
+        ax.plot(labels, batting_average, marker='o', linestyle='-', color='#FFA500', linewidth=2)
+        ax.set_ylabel("Batting Average", fontsize=12)
+        ax.set_title(f"Batting Average of {selected_player}", fontsize=14)
         st.pyplot(fig)
 
         # Histogram - Distribution of Runs Scored by All Players in ODIs
         fig, ax = plt.subplots()
-        sns.histplot(df["batting_Runs_ODI"], bins=20, kde=True, color='green', ax=ax)
-        ax.set_xlabel("Runs Scored")
-        ax.set_ylabel("Frequency")
-        ax.set_title("Distribution of Runs Scored in ODIs (All Players)")
+        sns.histplot(df["batting_Runs_ODI"], bins=20, kde=True, color='#3CB371', ax=ax)
+        ax.set_xlabel("Runs Scored", fontsize=12)
+        ax.set_ylabel("Frequency", fontsize=12)
+        ax.set_title("Distribution of Runs Scored in ODIs (All Players)", fontsize=14)
         st.pyplot(fig)
-    else:
-        st.error("Player not found! Please enter a valid player name.")
 
+    else:
+        st.error("🚨 Player not found! Please enter a valid player name.")