Create visuals.py

visuals.py

@@ -0,0 +1,44 @@
+# visuals.py
+import plotly.express as px
+import streamlit as st
+import pandas as pd
+
+def render_summary(df: pd.DataFrame):
+    st.header("Summary Statistics")
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        st.metric("Total Asteroids", len(df))
+    with col2:
+        hazardous_count = df['is_hazardous'].sum()
+        st.metric("Potentially Hazardous", f"{hazardous_count} ({hazardous_count/len(df)*100:.1f}%)")
+    with col3:
+        st.metric("Avg. Size", f"{df['avg_diameter_km'].mean():.2f} km")
+
+def render_visualizations(df: pd.DataFrame):
+    st.header("Visualizations")
+    viz_tab1, viz_tab2 = st.tabs(["Size Distribution", "Miss Distance"])
+
+    with viz_tab1:
+        fig1 = px.histogram(
+            df, x="avg_diameter_km", color="is_hazardous",
+            title="Size Distribution of Near-Earth Objects",
+            labels={"avg_diameter_km": "Average Diameter (km)", "is_hazardous": "Potentially Hazardous"},
+            color_discrete_map={True: "red", False: "green"}
+        )
+        st.plotly_chart(fig1, use_container_width=True)
+
+    with viz_tab2:
+        fig2 = px.scatter(
+            df, x="miss_distance_km", y="avg_diameter_km", color="is_hazardous",
+            size="relative_velocity_kph", hover_name="name",
+            title="Miss Distance vs. Size (with velocity)",
+            labels={
+                "miss_distance_km": "Miss Distance (km)",
+                "avg_diameter_km": "Average Diameter (km)",
+                "is_hazardous": "Potentially Hazardous",
+                "relative_velocity_kph": "Velocity (km/h)"
+            },
+            color_discrete_map={True: "red", False: "green"}
+        )
+        fig2.update_layout(xaxis_type="log")
+        st.plotly_chart(fig2, use_container_width=True)