Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,100 @@
-import altair as alt
-import numpy as np
+import os
 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 modules
+from scripts.featureEngineering import add_flight_day
+from scripts.stats import tidy_from_wide, analyze_r1_vs_L
+from scripts.graphMaking import make_figure
+
+# Load Data
+def list_final_data(folder="final_data"):
+    """Return list of CSV files in final_data folder."""
+    return [f for f in os.listdir(folder) if f.endswith(".csv")]
+
+def load_final_data(fname, folder="final_data"):
+    """Load selected CSV file as pandas DataFrame."""
+    path = os.path.join(folder, fname)
+    return pd.read_csv(path)
+
+# Main App
+def main():
+    st.title("Astronaut Biochemistry Dashboard")
+
+    # 1. Sidebar file selection
+    st.sidebar.header("Data Selection")
+    csv_files = list_final_data()
+
+    if not csv_files:
+        st.error("No CSV files found in final_data/")
+        return
+
+    selected_file = st.sidebar.selectbox("Choose dataset", csv_files)
+    df_raw = load_final_data(selected_file)
+    st.write(f"Loaded file: **{selected_file}**")
+
+    # 2. Clean with feature engineering
+    df_clean = add_flight_day(df_raw)
+
+    # 3. Transform to tidy format + run stats
+    tidy_df = tidy_from_wide(df_clean)
+    stats_df = analyze_r1_vs_L(tidy_df)
+
+    # 4. Sidebar user selections
+    st.sidebar.header("Plot Controls")
+
+    analyte = st.sidebar.selectbox(
+        "Select Analyte",
+        options=tidy_df["analyte"].unique().tolist(),
+        index=tidy_df["analyte"].unique().tolist().index("sodium")
+        if "sodium" in tidy_df["analyte"].unique() else 0
+    )
+
+    astronauts = st.sidebar.multiselect(
+        "Select Astronauts",
+        # Normalize IDs to uppercase for consistency
+        options=sorted([a.upper() for a in tidy_df["astronautID"].unique().tolist()]),
+        default=[]
+    )
+    astronauts = [a.upper() for a in astronauts]
+
+    sex_filter = st.sidebar.radio(
+        "Sex Filter",
+        ["All", "Male", "Female"],
+        index=0
+    )
+
+    show_error = st.sidebar.radio(
+        "Error Band",
+        ["None", "within", "group"],
+        index=0
+    )
+    show_error = None if show_error == "None" else show_error
+
+    # Unify filters: Astronauts take priority, else fall back to sex filter
+    if astronauts:
+        astronaut_filter = astronauts
+    elif sex_filter != "All":
+        astronaut_filter = sex_filter
+    else:
+        astronaut_filter = None
+
+    # 5. Generate figure
+    if analyte:
+        fig = make_figure(
+            tidy_df=tidy_df,
+            stats_df=stats_df,
+            analytes=[analyte],
+            astronaut_filter=astronaut_filter,
+            show_error=show_error
+        )
+        st.plotly_chart(fig, use_container_width=True)
+    else:
+        st.warning("Please select at least one analyte to plot.")
+
+    # 6. Optional: preview data
+    with st.expander("Preview Data"):
+        st.dataframe(tidy_df.head(20))
+
+if __name__ == "__main__":
+    main()