Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,30 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+import eda
+import models
+
+
+page = st.sidebar.selectbox(label='Select Page:', options=['Home Page', 'Exploration Data Analysis', 'Model Prediksi'])
+
+if page == 'Home Page':
+    st.header('Welcome Page') 
+    st.write('')
+    st.write('Milestone 2')
+    st.write('Nama      : M. Rachman')
+    st.write('Batch     : ')
+    st.write('Tujuan Milestone    : ')
+    st.write('')
+    st.caption('Silahkan pilih menu lain di Select Box pada sebelah kiri layar anda untuk memulai!')
+    st.write('')
+    st.write('')
+    with st.expander("Latar Belakang"):
+        st.caption('lorem ipsum')
+
+    with st.expander("Problem Statement"):
+            st.caption('lorem ipsum')
+
+    with st.expander("Kesimpulan"):
+        st.caption('lorem ipsum')
+elif page == 'Exploration Data Analysis':
+    eda.run()
+else:
+     models.run()