app.py

import streamlit as st
import pandas as pd
from Utility.data_loader import (
    load_train_series, load_train_events, 
    load_sample_submission, load_test_series
)

st.set_page_config(page_title="Sensor Data Viewer", layout="wide")
st.title("Sensor Data Viewer")

# --- Sidebar Radio Button ---
st.header("Select Dataset to View")
option = st.radio(
    "Choose a dataset:",
    ("Train Events", "Sample Submission", "Train Series", "Test Series", "Summary")
)

# --- Load and Show Data Based on Selection ---
df = None

if option == "Train Events":
    df = load_train_events()
    st.subheader("Train Events")
    st.dataframe(df.head())

elif option == "Sample Submission":
    df = load_sample_submission()
    st.subheader("Sample Submission")
    st.dataframe(df.head())

elif option == "Train Series":
    df = load_train_series()
    st.subheader("Train Series (1M rows sample)")
    st.dataframe(df.head())

elif option == "Test Series":
    df = load_test_series()
    st.subheader("Test Series")
    st.dataframe(df.head())

elif option == "Summary":
    st.subheader("Summary of All Key Datasets")

    with st.expander("📄 Train Events"):
        df_events = load_train_events()
        st.dataframe(df_events.head())
        st.write("Summary:")
        st.dataframe(df_events.describe(include="all"))

    with st.expander("📄 Sample Submission"):
        df_sample = load_sample_submission()
        st.dataframe(df_sample.head())
        st.write("Summary:")
        st.dataframe(df_sample.describe(include="all"))

    with st.expander("📄 Train Series"):
        df_series = load_train_series()
        st.dataframe(df_series.head())
        st.write("Summary:")
        st.dataframe(df_series.describe())

    with st.expander("📄 Test Series"):
        df_test = load_test_series()
        st.dataframe(df_test.head())
        st.write("Summary:")
        st.dataframe(df_test.describe())

# Footer
#st.markdown("---")
# st.caption("Developed by [Name] | Streamlit App for Sensor Data Exploration")