Spaces:
Running
Running
Download run.py from gradio/plot_guide_temporal_main: direct link, hf CLI and curl.
- Browser
- Download file 594 Bytes
-
https://huggingface.co/spaces/gradio/plot_guide_temporal_main/resolve/0781aaa47adf1fc5cfdf677d1f2091c2eefecb4e/run.py
- Command line
-
hf download hf://spaces/gradio/plot_guide_temporal_main@0781aaa47adf1fc5cfdf677d1f2091c2eefecb4e/run.py
-
curl -L -o run.py https://huggingface.co/spaces/gradio/plot_guide_temporal_main/resolve/0781aaa47adf1fc5cfdf677d1f2091c2eefecb4e/run.py
594 Bytes
| import gradio as gr | |
| import pandas as pd | |
| import numpy as np | |
| import random | |
| from datetime import datetime, timedelta | |
| now = datetime.now() | |
| df = pd.DataFrame({ | |
| 'time': [now - timedelta(minutes=5*i) for i in range(25)], | |
| 'price': np.random.randint(100, 1000, 25), | |
| 'origin': [random.choice(["DFW", "DAL", "HOU"]) for _ in range(25)], | |
| 'destination': [random.choice(["JFK", "LGA", "EWR"]) for _ in range(25)], | |
| }) | |
| with gr.Blocks() as demo: | |
| gr.LinePlot(df, x="time", y="price") | |
| gr.ScatterPlot(df, x="time", y="price", color="origin") | |
| if __name__ == "__main__": | |
| demo.launch() |