"I understand how you specify specific ticks to show in Bokeh, but my question is if there is a way to assign a specific label to show versus the position. So for example
plot.xaxis[0].ticker=FixedTicker(ticks=[0,1])
``
will only show the x-axis labels at 0 and 1, but what if instead of showing 0 and 1 I wanted to show Apple and Orange. Something like
Can you provide the code you tried to use with FuncTickFormatter.from_py_func? Its hard to say much if speculation is needed, and providing real code is the quickest, fastest way to avoid needing to speculate.
There was also a recent PR concerning this feature:
So it may be that you will need to try a dev build or wait for the next release (although, again, I can't say for sure if this PR has anything to do with your situation without seeing the code you tried with FuncTickFormatter.from_py_func)
Thanks,
Bryan
···
On Oct 27, 2016, at 1:57 PM, Satish Kumar <[email protected]> wrote:
"I understand how you specify specific ticks to show in Bokeh, but my question is if there is a way to assign a specific label to show versus the position. So for example
plot.xaxis[0].ticker=FixedTicker(ticks=[0,1])
will only show the x-axis labels at 0 and 1, but what if instead of showing 0 and 1 I wanted to show Apple and Orange. Something like
plot.xaxis[0].ticker=FixedTicker(ticks=[0,1], labels=['Apple', 'Orange'])
"
Apparently, FuncTickFormatter.from_py_func() raises ValueError: Function 'func' may only contain keyword arguments in bokeh version 0.12.3.