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96 lines
2.5 KiB
Python
96 lines
2.5 KiB
Python
import gradio as gr
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from vega_datasets import data
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stocks = data.stocks()
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gapminder = data.gapminder()
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gapminder = gapminder.loc[
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gapminder.country.isin(["Argentina", "Australia", "Afghanistan"])
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]
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climate = data.climate()
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seattle_weather = data.seattle_weather()
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## Or generate your own fake data, here's an example for stocks:
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#
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# import pandas as pd
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# import random
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#
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# stocks = pd.DataFrame(
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# {
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# "symbol": [
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# random.choice(
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# [
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# "MSFT",
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# "AAPL",
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# "AMZN",
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# "IBM",
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# "GOOG",
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# ]
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# )
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# for _ in range(120)
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# ],
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# "date": [
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# pd.Timestamp(year=2000 + i, month=j, day=1)
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# for i in range(10)
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# for j in range(1, 13)
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# ],
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# "price": [random.randint(10, 200) for _ in range(120)],
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# }
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# )
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def line_plot_fn(dataset):
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if dataset == "stocks":
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return gr.LinePlot(
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stocks,
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x="date",
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y="price",
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color="symbol",
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title="Stock Prices",
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tooltip=["date", "price", "symbol"],
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height=300,
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)
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elif dataset == "climate":
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return gr.LinePlot(
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climate,
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x="DATE",
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y="HLY-TEMP-NORMAL",
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y_lim=[250, 500],
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title="Climate",
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tooltip=["DATE", "HLY-TEMP-NORMAL"],
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height=300,
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)
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elif dataset == "seattle_weather":
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return gr.LinePlot(
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seattle_weather,
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x="date",
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y="temp_min",
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tooltip=["weather", "date"],
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title="Seattle Weather",
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height=300,
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)
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elif dataset == "gapminder":
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return gr.LinePlot(
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gapminder,
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x="year",
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y="life_expect",
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color="country",
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title="Life expectancy for countries",
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x_lim=[1950, 2010],
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tooltip=["country", "life_expect"],
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height=300,
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)
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with gr.Blocks() as line_plot:
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with gr.Row():
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with gr.Column():
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dataset = gr.Dropdown(
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choices=["stocks", "climate", "seattle_weather", "gapminder"],
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value="stocks",
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)
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with gr.Column():
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plot = gr.LinePlot()
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dataset.change(line_plot_fn, inputs=dataset, outputs=plot)
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line_plot.load(fn=line_plot_fn, inputs=dataset, outputs=plot)
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if __name__ == "__main__":
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line_plot.launch()
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