I’m searching for the same answers (lack of documentation makes it difficult). In answer, to question #1, what is the utility of “extra_generated_classes”: tl;dr extra_generated_classes defines a modulename, classname, and parentname used in template generating js/html code, and extends the parent class passed into the app class (usually HBox or VBox in the examples). Longer … Read more
Solution is to replace calls to show by calls to save.
Using the Embedding Bokeh Plots documentation example as suggested by Fabio Pliger, one can do this in Django: in the views.py file, we put: from django.shortcuts import render from bokeh.plotting import figure from bokeh.resources import CDN from bokeh.embed import components def simple_chart(request): plot = figure() plot.circle([1,2], [3,4]) script, div = components(plot, CDN) return render(request, “simple_chart.html”, … Read more
If you want to remove the logo and the toolbar you can do: p.toolbar.logo = None p.toolbar_location = None Hope this resolves your problem
It is probably easiest to just get the list of colors and cycle it yourself using itertools: import numpy as np from bokeh.plotting import figure, output_file, show # select a palette from bokeh.palettes import Dark2_5 as palette # itertools handles the cycling import itertools output_file(‘bokeh_cycle_colors.html’) p = figure(width=400, height=400) x = np.linspace(0, 10) # create … Read more
Thanks to this page in Google Groups I figured out how this can be done. Link here Edit 2015-10-20: looks like the google group link doesn’t work anymore unfortunately. It was a message from Sarah Bird @bokehplot. Edit 2017-01-18: Currently this would add multiple hover tool icons to the tool bar. This may cause problems. … Read more
Below is what I came up with. Its not pretty but it works. Im still new to Bokeh (& Python for that matter) so if anyone wants to suggest a better way to do this, please feel free. import pandas as pd import numpy as np from bokeh.charts import TimeSeries from bokeh.models import HoverTool from … Read more
Create a figure object. So, in your example the figure object is p1, then p1.axis.visible = False If you want to specify a y or x axis, then use p1.xaxis.visible = False or p1.yaxis.visible = False
I had the same error and I debugged the problem: I had NaN values in my plotted dataset and bokeh‘s serialize_json() function (in /core/json_encoder.py) does not allow NaN values (I don’t know why…). In the return part of this function there is the allow_nan=False argument in json.dumps() :(( The problem occurs only at the io … Read more
As of Bokeh 0.11.1, the user’s guide section on axes now shows how to edit properties of existing axes. The way to do it is the same as before: p = figure(width=300, height=300, x_axis_label=”Initial xlabel”) p.xaxis.axis_label=”New xlabel”