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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
),
)
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)
# def greet(name, intensity):
# return "Hello " + name + "!" * int(intensity)
# demo = gr.Interface(
# fn=greet,
# inputs=["text", "slider"],
# outputs=["text"]
# )
demo.launch(share=True)
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