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Archived discussions · Captured October 28, 2026

weird caching of previous plots in new images

Community Support
gkotsis
gkotsis

Greetings,

I have been experimenting with bokeh for a few days now and I have noticed this weird behaviour:

The figure which shows the plot objects may contain plot objects from previous figures.

Unfortunately, I cannot share the exact code, but this is the core of my program:

    from bokeh.plotting import scatter, line, hold, show

    from bokeh.resources import CDN

    from bokeh.embed import components

    import pandas as pd

    measurement = "..."

    df = ...

    hold()

    s = scatter(df['date'], df['value'], size=5, color="red", alpha=0.5, plot_width=600, plot_height=400, x_axis_type='datetime', legend="daily", title=measurement)

    l = line(df['date'], df['value'].mean(), line_width=2, color="grey", alpha=0.5, plot_width=600, plot_height=400, x_axis_type='datetime', legend="total")

    show()

    script, div = components(l, CDN)

    body = div + script

As you can see, I am embedding the graphic into an HTML webpage.

Any idea on what I am doing wrong?

Many thanks!

⌁   Link to post
Jared_Thompson
Jared_Thompson

if you are referring to the Scatter and the line being on the same chart?
If so the hold() is allowing that.

···

On Thu, Oct 23, 2014 at 7:31 AM, gkotsis@gmail.com wrote:

Greetings,

I have been experimenting with bokeh for a few days now and I have noticed this weird behaviour:

The figure which shows the plot objects may contain plot objects from previous figures.

Unfortunately, I cannot share the exact code, but this is the core of my program:

    from bokeh.plotting import scatter, line, hold, show
    from bokeh.resources import CDN
    from bokeh.embed import components
    import pandas as pd
    measurement = "..."
    df = ...
    hold()
    s = scatter(df['date'], df['value'], size=5, color="red", alpha=0.5, plot_width=600, plot_height=400, x_axis_type='datetime', legend="daily", title=measurement)
    l = line(df['date'], df['value'].mean(), line_width=2, color="grey", alpha=0.5, plot_width=600, plot_height=400, x_axis_type='datetime', legend="total")
    show()
    script, div = components(l, CDN)
    body = div + script

As you can see, I am embedding the graphic into an HTML webpage.

Any idea on what I am doing wrong?

Many thanks!

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⌁   Link to post
Damian_Avila
Damian_Avila

I guess you are referring to the accumulation of figures in your html file…

Right now, since 0.7 release, the plotting API was rewritten in a way that you will not have this problem again.

Just update the code to use the new plotting API and you will be fine.

Cheers.

Damian

···

On Sunday, October 26, 2014 1:53:36 PM UTC-3, Jared Thompson wrote:

if you are referring to the Scatter and the line being on the same chart?
If so the hold() is allowing that.

On Thu, Oct 23, 2014 at 7:31 AM, gkotsis@gmail.com wrote:

Greetings,

I have been experimenting with bokeh for a few days now and I have noticed this weird behaviour:

The figure which shows the plot objects may contain plot objects from previous figures.

Unfortunately, I cannot share the exact code, but this is the core of my program:

    from bokeh.plotting import scatter, line, hold, show
    from bokeh.resources import CDN
    from bokeh.embed import components
    import pandas as pd
    measurement = "..."
    df = ...
    hold()
    s = scatter(df['date'], df['value'], size=5, color="red", alpha=0.5, plot_width=600, plot_height=400, x_axis_type='datetime', legend="daily", title=measurement)
    l = line(df['date'], df['value'].mean(), line_width=2, color="grey", alpha=0.5, plot_width=600, plot_height=400, x_axis_type='datetime', legend="total")
    show()
    script, div = components(l, CDN)
    body = div + script

As you can see, I am embedding the graphic into an HTML webpage.

Any idea on what I am doing wrong?

Many thanks!

–

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To unsubscribe from this group and stop receiving emails from it, send an email to bokeh+unsubscribe@continuum.io.

To post to this group, send email to bokeh@continuum.io.

To view this discussion on the web visit https://groups.google.com/a/continuum.io/d/msgid/bokeh/589d2573-6793-4a94-bd2a-1b3838d95ba9%40continuum.io.

For more options, visit https://groups.google.com/a/continuum.io/d/optout.

⌁   Link to post

End of archived discussion · Replies are disabled