|
import gradio as gr |
|
from data import temp_sensor_data, food_rating_data |
|
|
|
with gr.Blocks() as scatter_plots: |
|
with gr.Row(): |
|
start = gr.DateTime("2021-01-01 00:00:00", label="Start") |
|
end = gr.DateTime("2021-01-05 00:00:00", label="End") |
|
apply_btn = gr.Button("Apply", scale=0) |
|
with gr.Row(): |
|
group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"], value="None", label="Group by") |
|
aggregate = gr.Radio(["sum", "mean", "median", "min", "max"], value="sum", label="Aggregation") |
|
|
|
temp_by_time = gr.ScatterPlot( |
|
temp_sensor_data, |
|
x="time", |
|
y="temperature", |
|
) |
|
temp_by_time_location = gr.ScatterPlot( |
|
temp_sensor_data, |
|
x="time", |
|
y="temperature", |
|
color="location", |
|
) |
|
|
|
time_graphs = [temp_by_time, temp_by_time_location] |
|
group_by.change( |
|
lambda group: [gr.ScatterPlot(x_bin=None if group == "None" else group)] * len(time_graphs), |
|
group_by, |
|
time_graphs |
|
) |
|
aggregate.change( |
|
lambda aggregate: [gr.ScatterPlot(y_aggregate=aggregate)] * len(time_graphs), |
|
aggregate, |
|
time_graphs |
|
) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
price_by_cuisine = gr.ScatterPlot( |
|
food_rating_data, |
|
x="cuisine", |
|
y="price", |
|
) |
|
with gr.Row(): |
|
price_by_rating = gr.ScatterPlot( |
|
food_rating_data, |
|
x="rating", |
|
y="price", |
|
color="wait", |
|
show_actions_button=True, |
|
) |
|
price_by_rating_color = gr.ScatterPlot( |
|
food_rating_data, |
|
x="rating", |
|
y="price", |
|
color="cuisine", |
|
|
|
) |
|
|
|
if __name__ == "__main__": |
|
scatter_plots.launch() |
|
|