import streamlit as st
import pandas as pd
import plotly.express as px

# App title
st.title("📊 Data Dashboard - CSV Viewer")
st.write("Upload a CSV file to explore data with summary stats and visualizations.")

# File uploader
uploaded_file = st.file_uploader("Choose a CSV file", type=["csv"])

if uploaded_file:
    # Load data
    df = pd.read_csv(uploaded_file)

    # Show raw data
    st.subheader("📁 Raw Data")
    st.dataframe(df)

    # Summary statistics
    st.subheader("📈 Summary Statistics")
    st.write(df.describe())

    # Column selection
    numeric_cols = df.select_dtypes(include='number').columns.tolist()
    categorical_cols = df.select_dtypes(include='object').columns.tolist()

    # Chart section
    st.subheader("📊 Visualizations")

    chart_type = st.selectbox("Choose a chart type", ["Histogram", "Bar Chart", "Scatter Plot"])

    if chart_type == "Histogram":
        col = st.selectbox("Select numeric column for histogram", numeric_cols)
        fig = px.histogram(df, x=col, title=f"Histogram of {col}")
        st.plotly_chart(fig)

    elif chart_type == "Bar Chart":
        col = st.selectbox("Select categorical column for bar chart", categorical_cols)
        fig = px.bar(df[col].value_counts().reset_index(),
                     x='index', y=col,
                     labels={'index': col, col: 'Count'},
                     title=f"Bar Chart of {col}")
        st.plotly_chart(fig)

    elif chart_type == "Scatter Plot":
        x_axis = st.selectbox("X-axis", numeric_cols, key='x')
        y_axis = st.selectbox("Y-axis", numeric_cols, key='y')
        fig = px.scatter(df, x=x_axis, y=y_axis, title=f"{y_axis} vs {x_axis}")
        st.plotly_chart(fig)

else:
    st.info("Please upload a CSV file to begin.")