Delete run.py

run.py

@@ -1,55 +0,0 @@
-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()