bokeh

问题 I'm gearing up towards using bokeh for an interactive online implementation of some python models I've written. Step 1 is understanding some basic interactive examples, but I can't get the introductory examples running INTERACTIVELY in a Jupyter notebook. I'm hoping someone can correct my misunderstanding of what is a copy-paste of bokeh's own example code. I'm aware that the Bokeh documentation isn't perfect (I fixed an outdated reference to bokeh.plotting.show rather than io.show ), but I

问题 I am plotting a complex interactive donut chart in bokeh. The code below is a simplification of a component of this chart. I have a function which compiles a dataframe of data for the donut, and then converts it to a CDS. This data is then plotted as annular wedges. A radiobutton group should trigger a switch to a different dataframe (as CDS), and replot the annular wedge glyphs. The example provide (for Jupyter Lab) works in one direction. When initially plotted the button.active == 0 (outer

问题 I am plotting a complex interactive donut chart in bokeh. The code below is a simplification of a component of this chart. I have a function which compiles a dataframe of data for the donut, and then converts it to a CDS. This data is then plotted as annular wedges. A radiobutton group should trigger a switch to a different dataframe (as CDS), and replot the annular wedge glyphs. The example provide (for Jupyter Lab) works in one direction. When initially plotted the button.active == 0 (outer

问题 I am plotting a complex interactive donut chart in bokeh. The code below is a simplification of a component of this chart. I have a function which compiles a dataframe of data for the donut, and then converts it to a CDS. This data is then plotted as annular wedges. A radiobutton group should trigger a switch to a different dataframe (as CDS), and replot the annular wedge glyphs. The example provide (for Jupyter Lab) works in one direction. When initially plotted the button.active == 0 (outer

问题 In Bokeh I am able to add a text annotation to each point in my plot programmatically by using LabelSet . Below I give an example for a simple bar plot: import numpy as np import pandas as pd # Make some data dat = \ (pd.DataFrame({'team':['a','b','c'], 'n_people':[10,5,12]}) .assign(n_people_percent = lambda x: (x['n_people']/np.sum(x['n_people'])*100) .round(1).astype('string') + '%') ) dat # Bar plot with text annotations for every bar from bkcharts import show, Bar from bkcharts

问题 Let me just start by complementing the HoloViews developers, this thing is pretty amazing. There are just a lot of pieces and it is a bit hard to figure out how to put them all together to do what I want:). I am trying here to do linked multidimensional data plotting, i.e. I want to have several plots showing views of the same data along various dimensions. I want then to harness the Bokeh selection tools to select data in one of the plots, and see where it is in the others. But I also need

问题 So I'm trying to create a Bokeh plot for which I would like to be able to manually adapt the range of the X-Axis with a slider. Being a newbie I've only managed to get this far and despite researching this subject I haven't been able to solve this problem. Here my code: from bokeh.layouts import column from bokeh.models import CustomJS, ColumnDataSource, Slider from bokeh.plotting import Figure, output_file, show output_file("test.html") x = [x*0.5 for x in range(0, 200)] y = x source =

问题 I'm using bokeh with an ipython notebook. I want to plot a line graph in bokeh using a pandas DataFrame containing datetimes: import pandas as pd from datetime import datetime as dt from bokeh.io import output_notebook from bokeh.charts import Bar, Line, show df = pd.DataFrame(data=[1,2,3], index=[dt(2015, 1, 1), dt(2015, 1, 2), dt(2015, 1, 3)], columns=['foo']) output_notebook() show(Line(df)) However, bokeh uses microseconds! Why is this? How do I fix it? 回答1: As of bokeh 0.12.3, you can

问题 I am making a Bokeh dashboard in Python 3, and one of my main plots in-progress is a scatterplot. I have the entire plot made, but I am looking for a way to have two sliders (x and y) to specify the range displayed based on where they are slid to. p6 = figure(title = 'Average Duration and Number of Calls by Topic in Top Departments', y_range=(0,13000), tools=["hover", 'box_zoom', 'reset', 'save'], tooltips="@Topic; @Seconds seconds of average duration; @Count total calls") My not working