Update src/streamlit_app.py

src/streamlit_app.py

@@ -184,6 +184,69 @@ menu = st.sidebar.selectbox(
     ["Home", "About", "Data", "Contact"]
 )
 
+### Use this one!!!
+# Plot 3: Line chart.
+df = df[df['year'] != 2025] # 2025 is not end, so the trend can't be see
+
+# Group the each crime type by year.
+yearly_crime_counts = (
+    df.groupby(["year", "crm_cd_desc"])
+    .size()
+    .reset_index(name="Count")
+)
+
+# Filter the crime types that have the most top 5 cases.
+top5_crimes = df["crm_cd_desc"].value_counts().nlargest(5).index
+filtered_crimes = yearly_crime_counts[yearly_crime_counts["crm_cd_desc"].isin(top5_crimes)]
+
+# Plot the line plot.
+line_chart = alt.Chart(filtered_crimes).mark_line(point=True).encode(
+    x=alt.X("year:O", title="Year"),
+    y=alt.Y("Count:Q", title="Number of Incidents"),
+    color=alt.Color("crm_cd_desc:N", title="Crime Type"),
+    tooltip=["year", "crm_cd_desc", "Count"]
+).properties(
+    title="Yearly Trends of Top 5 Crime Types",
+    width=700,  
+    height=400
+)
+
+# Display the plot.
+line_chart
+
+### Use this one!!!
+# Identify top 10 crime types
+top_10_crimes = df['crm_cd_desc'].value_counts().nlargest(10).index.tolist()
+
+# Filter the main DataFrame to include only top 10 crimes
+df_top = df[df['crm_cd_desc'].isin(top_10_crimes)]
+
+# Create the dropdown.
+crime_dropdown = ipywidgets.Dropdown(
+    options= sorted(top_10_crimes),
+    description="Crime Type:")
+
+# Create the map.
+def crime_map(year, crime):
+    df_filtered = df[(df['year'] == year) & (df['crm_cd_desc'] == crime)].sample(n=300, random_state=1)
+    gdf_points = gpd.GeoDataFrame(
+        df_filtered,
+        geometry=gpd.points_from_xy(df_filtered['lon'], df_filtered['lat']),
+        crs="EPSG:4326"
+    )
+    
+    fig, ax = plt.subplots(figsize=(10, 10))
+    gdf_counties.plot(ax=ax, color='lightgray', edgecolor='white')
+    gdf_points.plot(ax=ax, color='red', markersize=10, alpha=0.6)
+    ax.set_title(f"{crime} - {year}")
+    ax.set_xlabel("Longitude")
+    ax.set_ylabel("Latitude")
+    plt.grid(True)
+    plt.show()
+    
+# Displat the plot.
+ipywidgets.interact(crime_map, year=year_dropdown, crime=crime_dropdown)
+
 # Define what each menu option does
 if menu == "Home":
     st.title("Analyze Crime Distributions")