Create run.py

run.py

@@ -0,0 +1,55 @@
+import gradio as gr
+import plotly.graph_objects as go
+from datasets import load_dataset
+
+dataset = load_dataset("gradio/NYC-Airbnb-Open-Data", split="train")
+df = dataset.to_pandas()
+
+def filter_map(min_price, max_price, boroughs):
+
+    filtered_df = df[(df['neighbourhood_group'].isin(boroughs)) & 
+          (df['price'] > min_price) & (df['price'] < max_price)]
+    names = filtered_df["name"].tolist()
+    prices = filtered_df["price"].tolist()
+    text_list = [(names[i], prices[i]) for i in range(0, len(names))]
+    fig = go.Figure(go.Scattermapbox(
+            customdata=text_list,
+            lat=filtered_df['latitude'].tolist(),
+            lon=filtered_df['longitude'].tolist(),
+            mode='markers',
+            marker=go.scattermapbox.Marker(
+                size=6
+            ),
+            hoverinfo="text",
+            hovertemplate='<b>Name</b>: %{customdata[0]}<br><b>Price</b>: $%{customdata[1]}'
+        ))
+
+    fig.update_layout(
+        mapbox_style="open-street-map",
+        hovermode='closest',
+        mapbox=dict(
+            bearing=0,
+            center=go.layout.mapbox.Center(
+                lat=40.67,
+                lon=-73.90
+            ),
+            pitch=0,
+            zoom=9
+        ),
+    )
+
+    return fig
+
+with gr.Blocks() as demo:
+    with gr.Column():
+        with gr.Row():
+            min_price = gr.Number(value=250, label="Minimum Price")
+            max_price = gr.Number(value=1000, label="Maximum Price")
+        boroughs = gr.CheckboxGroup(choices=["Queens", "Brooklyn", "Manhattan", "Bronx", "Staten Island"], value=["Queens", "Brooklyn"], label="Select Boroughs:")
+        btn = gr.Button(value="Update Filter")
+        map = gr.Plot()
+    demo.load(filter_map, [min_price, max_price, boroughs], map)
+    btn.click(filter_map, [min_price, max_price, boroughs], map)
+
+if __name__ == "__main__":
+    demo.launch()