make app simpler

app.py

@@ -1,28 +1,11 @@
 import streamlit as st
 import pandas as pd
-import matplotlib.pyplot as plt
 
-# Load the data
-df = pd.read_excel("metrics.xlsx")
-
-st.title("Ontology Benchmark Metrics Viewer")
 
-# Show the dataset
-st.subheader("Metrics Table")
-st.dataframe(df, use_container_width=True)
+st.title("OntoLearner Benchmark Metrics")
 
-# Drop non-numeric columns for metric selection
-numeric_cols = df.select_dtypes(include=['float64', 'int64']).columns.tolist()
-
-# Select a metric to visualize
-st.subheader("Metric Visualization")
-selected_metric = st.selectbox("Select a metric column:", numeric_cols)
+# Load the Excel file
+df = pd.read_excel("metrics.xlsx")
 
-# 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)
+# Display as a table
+st.dataframe(df, use_container_width=True)