diff --git a/community_gallery/earthquakes/hello.py b/community_gallery/earthquakes/hello.py
index 6b1cb3da7..0197b46b5 100644
--- a/community_gallery/earthquakes/hello.py
+++ b/community_gallery/earthquakes/hello.py
@@ -3,7 +3,6 @@
 
 from preswald import connect, get_df, plotly, slider, table, text
 
-
 # Title
 text("# Earthquake Analytics Dashboard 🌍")
 
@@ -49,6 +48,7 @@
 
 # table(c_data)
 # table(d_data)
+
 # ---
 
 # Slider for filtering magnitude
@@ -57,7 +57,6 @@
 # Read the data and filter based on magnitude
 data = get_df("earthquake_data")
 # data = get_df("earthquake_db", "earthquake_data") # NOTE: requires changing the column names based on what you have in postgres
-# Convert Magnitude column to numeric, handling any non-numeric values
 data["Magnitude"] = pd.to_numeric(data["Magnitude"], errors="coerce")
 filtered_data = data[data["Magnitude"] >= min_magnitude]
 
@@ -67,7 +66,6 @@
 # Summary statistics
 text(f"### Total Earthquakes with Magnitude ≥ {min_magnitude}: {len(filtered_data)}")
 
-
 # Interactive map using Plotly
 text("## Earthquake Locations")
 fig_map = px.scatter_geo(
@@ -83,7 +81,14 @@
 
 # Magnitude distribution
 fig_hist = px.histogram(
-    filtered_data, x="Magnitude", nbins=20, title="Distribution of Magnitudes"
+    filtered_data,
+    x="Magnitude",
+    nbins=20,
+    title="Distribution of Magnitudes"
+)
+fig_hist.update_layout(  # 🆕 Add x/y axis labels
+    xaxis_title="Magnitude",
+    yaxis_title="Number of Earthquakes"
 )
 plotly(fig_hist)
 
diff --git a/community_gallery/travel/hello.py b/community_gallery/travel/hello.py
index 14d24d134..c602636cd 100644
--- a/community_gallery/travel/hello.py
+++ b/community_gallery/travel/hello.py
@@ -3,7 +3,6 @@
 
 from preswald import connect, get_df, plotly, slider, table, text
 
-
 # Title
 text("# Travel Details Analytics Dashboard 🌍")
 
@@ -81,6 +80,10 @@ def clean_cost(cost):
     nbins=20,
     title="Distribution of Accommodation Cost",
 )
+fig_hist.update_layout(  # ✅ Added axis titles for Issue #656
+    xaxis_title="Accommodation Cost (USD)",
+    yaxis_title="Number of Trips"
+)
 plotly(fig_hist)
 
 # Nationality vs. Accommodation cost scatter plot