bokeh

Objective: I want to have tick marks on the x axis only on 2017/10/2 and 2017/10/5. One constraint is that my times are not guaranteed to be evenly separated, so converting to a string and doing a categorical axis is not possible. They need to be numeric/datetime. Problem: I'm unsure how to properly format the desired dates so they are rendered properly by Bokeh. I've tried dividing by 10 ** 9 and such to convert to milliseconds. This has not worked. Sample Code: from bokeh.plotting import figure, show from bokeh.models import FixedTicker import pandas as pd import numpy as np y = list(range(3

When Bokeh tools are available, one is always selected by default (normally "pan"). Is there a way to have all tools be deselected while still making them available? This way the reader is less likely to mess up the plot by accident, especially on a small mobile device. As of Bokeh 0.12 or so, it is possible to configure which tools are active : # configure so that no drag tools are active plot.toolbar.active_drag = None # configure so that Bokeh chooses what (if any) scroll tool is active plot.toolbar.active_scroll = "auto" # configure so that a specific PolySelect tap tool is active plot

A nice thing about Bokeh is that callbacks can be specified from the Python layer that result actions on the javascript level without the need of bokeh-server. So one can create interactive widgets that run in a browser without an Ipython or Bokeh server running. The 0.9.3. documentation gives an example that I can reproduce in an ipython notebook: http://docs.bokeh.org/en/latest/docs/user_guide/interaction.html#cutomjs-for-widgets from bokeh.io import vform from bokeh.models import CustomJS, ColumnDataSource, Slider from bokeh.plotting import figure, output_file, show output_file("callback

I am new to pandas and bokeh and I am trying to create a scatter plot from a pandas dataframe. However, I keep getting the following error: new_data[colname] = df[colname].tolist() AttributeError: 'DataFrame' object has no attribute 'tolist' Using the dummy data from bokeh (from bokeh.sampledata.iris import flowers as data) the scatter works fine. type tsneX tsneY +50.000 columns 0 A 53.828863 20.740931 1 B 57.816909 18.478468 2 A 55.913429 22.948167 3 C 56.603005 15.738954 scatter = Scatter(df, x='tsneX', y='tsneY', color='type', marker='type', title='t-sne', legend=True) Edit: I'm not using

I am using the Bokeh package to generate maps to show the results of a simulation. The output is individual maps in html format with interactivity. The interactivity is needed for individual maps. See this link for an example: http://docs.bokeh.org/en/0.10.0/docs/gallery/texas.html The simulation can automatically be set to run a number of times and will produce a map for each run. This could be 100's of maps. I would like to be able to stitch together the maps to create a movie - the interactivity is not required for this. Bokeh has functionality to create PNG files via the browser so it is

I have an array of certain events with time stamp and want to create a heatmap: x axis should represent the date, f.e. '2016-02-03', y axis should represent the hour of occurrence, f.e. 13 (if 13:32), the color should depend on the count of occurred event. My data (as pandas dataframe z.head() ): date hour i 0 2016-01-15 13 1 1 2016-01-15 13 1 2 2016-01-15 12 1 3 2016-01-15 10 1 4 2016-01-15 10 1 My failed attempt: from bokeh._legacy_charts import HeatMap, output_file, show hm = HeatMap(z.head(), x='date', y='hour', values='i', stat='count') And the exception: AttributeError Traceback (most