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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")
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