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import gradio as gr |
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import xyzservices.providers as xyz |
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from bokeh.models import ColumnDataSource, Whisker |
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from bokeh.plotting import figure |
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from bokeh.sampledata.autompg2 import autompg2 as df |
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from bokeh.sampledata.penguins import data |
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from bokeh.transform import factor_cmap, jitter, factor_mark |
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def get_plot(plot_type): |
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if plot_type == "map": |
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plot = figure( |
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x_range=(-2000000, 6000000), |
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y_range=(-1000000, 7000000), |
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x_axis_type="mercator", |
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y_axis_type="mercator", |
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) |
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plot.add_tile(xyz.OpenStreetMap.Mapnik) |
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return plot |
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elif plot_type == "whisker": |
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classes = sorted(df["class"].unique()) |
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p = figure( |
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height=400, |
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x_range=classes, |
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background_fill_color="#efefef", |
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title="Car class vs HWY mpg with quintile ranges", |
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) |
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p.xgrid.grid_line_color = None |
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g = df.groupby("class") |
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upper = g.hwy.quantile(0.80) |
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lower = g.hwy.quantile(0.20) |
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source = ColumnDataSource(data=dict(base=classes, upper=upper, lower=lower)) |
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error = Whisker( |
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base="base", |
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upper="upper", |
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lower="lower", |
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source=source, |
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level="annotation", |
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line_width=2, |
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) |
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error.upper_head.size = 20 |
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error.lower_head.size = 20 |
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p.add_layout(error) |
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p.circle( |
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jitter("class", 0.3, range=p.x_range), |
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"hwy", |
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source=df, |
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alpha=0.5, |
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size=13, |
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line_color="white", |
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color=factor_cmap("class", "Light6", classes), |
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) |
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return p |
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elif plot_type == "scatter": |
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SPECIES = sorted(data.species.unique()) |
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MARKERS = ["hex", "circle_x", "triangle"] |
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p = figure(title="Penguin size", background_fill_color="#fafafa") |
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p.xaxis.axis_label = "Flipper Length (mm)" |
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p.yaxis.axis_label = "Body Mass (g)" |
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p.scatter( |
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"flipper_length_mm", |
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"body_mass_g", |
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source=data, |
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legend_group="species", |
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fill_alpha=0.4, |
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size=12, |
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marker=factor_mark("species", MARKERS, SPECIES), |
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color=factor_cmap("species", "Category10_3", SPECIES), |
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) |
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p.legend.location = "top_left" |
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p.legend.title = "Species" |
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return p |
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with gr.Blocks() as demo: |
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with gr.Row(): |
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plot_type = gr.Radio(value="scatter", choices=["scatter", "whisker", "map"]) |
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plot = gr.Plot() |
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plot_type.change(get_plot, inputs=[plot_type], outputs=[plot]) |
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demo.load(get_plot, inputs=[plot_type], outputs=[plot]) |
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if __name__ == "__main__": |
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demo.launch() |
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