Update app.py

app.py

@@ -48,9 +48,12 @@ elif option == "Plots":
     st.subheader("Job Category Distribution")
     category_counts = jobs_df[category_column].value_counts()
 
+    # Create a color palette for the bars
+    colors = plt.cm.Paired.colors  # You can choose any colormap you prefer
+
     # Create the bar plot
     fig1, ax1 = plt.subplots(figsize=(10, 6))  # Set figure size
-    bars = ax1.bar(category_counts.index, category_counts.values, color='skyblue')
+    bars = ax1.bar(category_counts.index, category_counts.values, color=colors[:len(category_counts)])
 
     ax1.set_xlabel("Job Category")
     ax1.set_ylabel("Number of Jobs")
@@ -61,6 +64,8 @@ elif option == "Plots":
     legend_labels = [f"{category}: {int(count)}" for category, count in zip(category_counts.index, category_counts.values)]
     ax1.legend(bars, legend_labels, title="Job Categories", loc="upper left", bbox_to_anchor=(1, 1))  # Position the legend
 
+    # No text labels on the bars and no labels above the bars
+
     # Adjust layout to give space for the legend
     plt.subplots_adjust(right=0.75)  # Adjust right margin for legend space
 
@@ -68,6 +73,7 @@ elif option == "Plots":
 
 
 
+
     # 2. Pie Chart for Category Distribution
     st.subheader("Job Category Proportions")
     fig2, ax2 = plt.subplots(figsize=(10, 10))  # Adjust the size as needed