app.py

import streamlit as st
import pandas as pd
import numpy as np
import plotly.express as px
import matplotlib.pyplot as plt
import seaborn as sns
import io

plt.style.use("ggplot")

st.set_page_config(page_title="UR CRISTIANO RONALDO (CR7) - Extensive EDA & Analytics", layout="wide")

st.sidebar.title("📊 UR Cristiano (CR7) Analytics")

st.sidebar.image("cr7.png", use_column_width=True)

sections = ["Introduction", 
"Basic Exploration", 
"Goals per Competition", 
"Goals per Season", 
"Goals per Club", 
"Goals per Playing Position", 
"Goals per Game Minute", 
"Goals per Type", 
"Scoreline After Goals",
"Opponents", 
"Favorite Opponents", 
"Assists", 
"Goals per Venue"]

selections = st.sidebar.radio("Navigate to", sections)


def load_data():
    df = pd.read_csv("data.csv")
    return df

df = load_data()

if selections == "Introduction":
    st.title("⚽ CR7 - Extensive EDA & Analytics")
    st.subheader("UR Cristiano Roanaldo - All Club Goals Statistics")

    st.write("""
    **Cristiano Ronaldo dos Santos Aveiro** is a Portuguese professional footballer who plays as a forward for Al-Nassr and captains the Portugal national team.
    
    - **Current team**: Al-Nassr (#7 / Forward)
    - **Born**: February 5, 1985 (age 39 years), Funchal, Portugal
    - **Height**: 1.87 m
    - **Partner**: Georgina Rodríguez (2017–)
    - **Salary**: 26.52 million GBP (2022)
    - **Children**: Cristiano Ronaldo Jr., Alana Martina, Eva Maria, Mateo Ronaldo
    """)


elif selections == "Basic Exploration":
    st.subheader("🔍 Basic Exploration")
    st.write("### Data Snapshot")
    st.dataframe(df.head())
    st.write("### Data Info")
    buffer = io.StringIO()
    df.info(buf = buffer)
    s = buffer.getvalue()
    st.text(s)

    st.write("### Unique Values in Each Column")
    st.dataframe(pd.DataFrame(df.apply(lambda col:len(col.unique())), columns = ["Unique Values Count"]))
    st.write("### Summary Statistics for Categorical Columns")
    st.dataframe(df.describe(include=['object']).T)

elif selections == "Goals per Competition":
    st.subheader("🏆 Goals per Competition")
    fig = px.histogram(df, x = 'Competition', color='Club', title = "Goals per Competition", 
                 height=500,hover_name = "Club", hover_data=['Competition', 'Club'])
    st.plotly_chart(fig)
    st.write("### Competition Goal Counts")
    st.dataframe(df.Competition.value_counts())

elif selections == "Goals per Season":
    st.subheader("📅 Goals per Season")
    fig = px.histogram(df, x = 'Season', color='Club', title = "Goals per Season", 
                 height=500,hover_name = "Club", hover_data=['Season', 'Club'])
    st.plotly_chart(fig)

elif selections == "Goals per Club":
    st.subheader("🏅 Goals per Club")
    fig1 = px.histogram(df, x = 'Club', color='Season', title = "Goals per Club - Season", 
                 height=500,hover_name = "Season", hover_data=['Competition', 'Season', 'Club'])
    fig2 = px.histogram(df, x = 'Club', color='Competition', title = "Goals per Club - Competition", 
                 height=500,hover_name = "Competition", hover_data=['Competition', 'Season', 'Club'])
    st.plotly_chart(fig1)
    st.plotly_chart(fig2)

elif selections == "Goals per Playing Position":
    st.subheader("⚽ Goals per Playing Position")
    fig = px.histogram(df, x = 'Playing_Position', color='Club', title = "Goals per Playing Position", 
                 height=500,hover_name = "Club", hover_data=['Playing_Position','Competition', 'Season', 'Club'])
    st.plotly_chart(fig)

elif selections == "Goals per Game Minute":
    st.subheader("⏰ Goals per Game Minute")
    df['Minute'] = df['Minute'].str.extract('(\d+)', expand=False).fillna(0).astype(int)
    bins = [0,15,30,45,60,75,90,105,120]
    labels = ['0-15', '15-30', '30-45', '45-60','60-75', '75-90', '90-105','105-120']
    df['Minute_Bin'] = pd.cut(df['Minute'], bins = bins, labels=labels, right=False)
    fig = px.histogram(df, x = 'Minute_Bin', title = "Goals per Game Minute", color = 'Club', height=500)
    st.plotly_chart(fig)

elif selections == "Goals per Type":
    st.subheader("🏹 Goals per Type")
    fig = px.histogram(df, x = 'Type', title = "Goals per Typee", color = 'Club', height=500)
    st.plotly_chart(fig)

elif selections == "Scoreline After Goals":
    st.subheader("🔢 Scoreline After Goals")
    top_20_scores = df['At_score'].value_counts().nlargest(20).index
    df_top_20 = df[df['At_score'].isin(top_20_scores)]

    fig, ax = plt.subplots(figsize=(15,7))
    sns.countplot(x='At_score', data=df_top_20, order = top_20_scores, ax = ax)
    ax.set_title("Top 20 Scoresheets after Scoring", fontsize = 20)
    st.pyplot(fig)

elif selections == "Opponents":
    st.subheader("🆚 Opponents")
    top_20_opponent = df['Opponent'].value_counts().nlargest(20).index
    df_top_20 = df[df['Opponent'].isin(top_20_opponent)]
    fig, ax = plt.subplots(figsize=(30,10))
    sns.countplot(x='Opponent', data = df_top_20, order = top_20_opponent, ax=ax)
    ax.set_title("Goal per Opponents", fontsize = 20)
    st.pyplot(fig)

elif selections == "Favorite Opponents":
    st.subheader("❤️ Favorite Opponents", )
    fig, ax = plt.subplots(figsize=(15,7))
    fav_opponents_df = df['Opponent'].value_counts()[df['Opponent'].value_counts()>15]
    sns.countplot(x='Opponent', data = df[df['Opponent'].isin(fav_opponents_df.index)], order = fav_opponents_df.index, ax=ax)
    ax.set_title("Favorite Opponents", fontsize = 20)
    st.pyplot(fig)

elif selections == "Assists":
    st.subheader("🤝 Assists")

    top_10_assist = df['Goal_assist'].value_counts().nlargest(10).index

    df_top_10 = df[df['Goal_assist'].isin(top_10_assist)]

    fig, ax = plt.subplots(figsize=(15,7))

    sns.countplot(x = 'Goal_assist', data = df_top_10, order = top_10_assist, ax = ax)

    ax.set_title("Top 10 Assists", fontsize = 20)

    st.pyplot(fig)

elif selections == "Goals per Venue":
    st.subheader("🏟️ Goals per Venue")
    fig, ax = plt.subplots(figsize = (15,7))
    sns.countplot(x = 'Venue', data = df, order = df['Venue'].value_counts().index, ax = ax)
    ax.set_title("Goal Per Venue", fontsize = 20)
    st.pyplot(fig)