import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import os
from io import StringIO

# Function to load the uploaded file (CSV or Excel)
def load_file(uploaded_file):
    """Load data from an uploaded file."""
    try:
        if uploaded_file.type == "text/csv":
            data = pd.read_csv(uploaded_file)
        elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet":
            data = pd.read_excel(uploaded_file)
        else:
            st.error("Unsupported file type.")
            return None
        return data
    except Exception as e:
        st.error(f"Error loading file: {e}")
        return None

# Function to generate graph based on user query
def generate_graph(data, query):
    """Generate a graph based on user query."""
    try:
        fig, ax = plt.subplots(figsize=(10, 6))

        if "bar" in query.lower() and "gross sales" in query.lower():
            # Bar chart for countries and gross sales
            if 'country' in data.columns and 'gross_sales' in data.columns:
                country_data = data[['country', 'gross_sales']].groupby('country').sum().reset_index()
                sns.barplot(x='country', y='gross_sales', data=country_data, ax=ax, color='skyblue')
                ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')
                st.pyplot(fig)
            else:
                st.error("The dataset must contain 'country' and 'gross_sales' columns.")
        elif "line" in query.lower() and "sales trend" in query.lower():
            # Line chart for sales trend over time
            if 'date' in data.columns and 'sales' in data.columns:
                data['date'] = pd.to_datetime(data['date'])
                sales_trend = data.groupby('date')['sales'].sum().reset_index()
                sns.lineplot(x='date', y='sales', data=sales_trend, ax=ax)
                ax.set_title("Sales Trend Over Time")
                st.pyplot(fig)
            else:
                st.error("The dataset must contain 'date' and 'sales' columns.")
        elif "scatter" in query.lower() and "relationship" in query.lower():
            # Scatter plot for relationships
            columns = query.lower().split("between")[-1].strip().split("and")
            x_col = columns[0].strip()
            y_col = columns[1].strip()

            if x_col in data.columns and y_col in data.columns:
                sns.scatterplot(x=x_col, y=y_col, data=data, ax=ax)
                ax.set_title(f"Scatter Plot: {x_col} vs {y_col}")
                st.pyplot(fig)
            else:
                st.error(f"The dataset must contain '{x_col}' and '{y_col}' columns.")
        elif "histogram" in query.lower():
            # Histogram for a specified column
            column = query.lower().split("for")[-1].strip()

            if column in data.columns:
                sns.histplot(data[column], bins=20, kde=True, ax=ax, color='green')
                ax.set_title(f"Histogram of {column}")
                st.pyplot(fig)
            else:
                st.error(f"The dataset must contain the column '{column}'.")
        else:
            st.error("Unsupported graph type. Try asking for a bar chart, line chart, scatter plot, or histogram.")
    except Exception as e:
        st.error(f"Error generating graph: {e}")

# Streamlit App Interface
def main():
    st.set_page_config(page_title="Data Visualization App", page_icon="📊", layout="wide")

    # Set background image
    st.markdown(
        """
        <style>
        .stApp {
            background-image: url('https://cdn.pixabay.com/photo/2016/06/02/02/33/triangles-1430105_1280.png');
            background-size: cover;
        }
        </style>
        """, unsafe_allow_html=True
    )

    st.title("Data Visualization App")
    st.markdown("Created by: Shamil Shahbaz", unsafe_allow_html=True)

    # File upload section
    uploaded_file = st.file_uploader("Upload a CSV or Excel file", type=["csv", "xlsx"])

    if uploaded_file is not None:
        # Load and display data
        data = load_file(uploaded_file)

        if data is not None:
            st.write("Dataset preview:", data.head())

            # User input for graph generation
            query = st.text_input("Enter your query (e.g., 'Generate a bar chart for countries and gross sales')")

            if query:
                # Generate the graph based on the query
                generate_graph(data, query)

if __name__ == "__main__":
    main()