update app.py

app.py

@@ -2,21 +2,27 @@ import streamlit as st
 import pandas as pd
 import matplotlib.pyplot as plt
 
-# Title
-st.title("Ontology Benchmark Metrics")
-
-# Load Excel file (assumed to be in the same directory)
+# Load the data
 df = pd.read_excel("metrics.xlsx")
 
-# Show Data
+st.title("Ontology Benchmark Metrics Viewer")
+
+# Show the dataset
 st.subheader("Metrics Table")
-st.dataframe(df)
+st.dataframe(df, use_container_width=True)
 
-# Visualization
-st.subheader("Metric Visualization")
-metric = st.selectbox("Select column to visualize:", df.columns[1:])
+# Drop non-numeric columns for metric selection
+numeric_cols = df.select_dtypes(include=['float64', 'int64']).columns.tolist()
 
-fig, ax = plt.subplots()
-df.plot(x=df.columns[0], y=metric, kind='bar', ax=ax)
-st.pyplot(fig)
+# Select a metric to visualize
+st.subheader("Metric Visualization")
+selected_metric = st.selectbox("Select a metric column:", numeric_cols)
 
+# Plot the metric per ontology
+fig, ax = plt.subplots(figsize=(10, 6))
+df_sorted = df.sort_values(by=selected_metric, ascending=False)
+ax.barh(df_sorted['Ontology ID'], df_sorted[selected_metric])
+ax.set_xlabel(selected_metric)
+ax.set_ylabel("Ontology ID")
+ax.set_title(f"{selected_metric} by Ontology")
+st.pyplot(fig)