bokeh

I have a bokeh (v0.11) serve app that produces a scatter plot using (x,y) coordinates from a data frame. I want to add interactions such that when a user either selects points on the plot or enters the name of comma-separated points in the text box (ie. "p55, p1234"), then those points will turn red on the scatter plot. I have found one way to accomplish this (Strategy #3, below) but it is terribly slow for large dataframes. I would think there is a better method. Can anyone help me out? Am I missing some obvious function call? Strategy 1 (<1ms for 100 points) drills into the ColumnDataSource

I want to make interactive plot in django views (or model ?). Let's say I want to use selection_histogram example. I think Bokeh fit my needs because, I have matplot/seaborn that I can reuse and I'm not pretty good at javascript. There was no problem for me to follow this example : how to embed standalone bokeh graphs into django templates . As I understand, I need to run a bokeh server and make some proxy using nginx How can I embed a interactive bokeh plot into a django view ? I tried this : Launch bokeh server bokeh serve --allow-websocket-origin=127.0.0.1:8001 selection_histogram.py Update

I've taken the below code from another source - it is not my own code. The code allows you to select a cell in the data table, and the 'downloads' data for that cell will chart based on the row of the cell selected. How do I expand this code such that if I have multiple variables (eg. 'downloads' and 'uploads') and so more columns in the data table, I can chart data based on that cell (so where row AND column are important)? Alternatively, how can I define as a variable the column number of a selected cell (in the same way selected_row below can be used to define the row number)? from datetime

I am trying to create a plot using bokeh to visualize my data on IPython Notebook. I want to add some widgets to make it more interactive. Below is an example of the codes. from bokeh.models import CustomJS, ColumnDataSource from bokeh.plotting import Figure, output_notebook, show from bokeh.models.widgets import Select from bokeh.layouts import column output_notebook() x = [x*0.005 for x in range(0, 200)] y = x z = ['A' if i>50 else 'B' for i in range(len(x))] source = ColumnDataSource(data=dict(x=x, y=y, z=z)) plot = Figure(plot_width=400, plot_height=400) plot.line('x', 'y', source=source,

I am trying to get a plot like a stock data in Bokeh like in the link http://bokeh.pydata.org/en/latest/docs/gallery/stocks.html 2004-01-05,00:00:00,01:00:00,Mon,20504,792 2004-01-05,01:00:00,02:00:00,Mon,16553,783 2004-01-05,02:00:00,03:00:00,Mon,18944,790 2004-01-05,03:00:00,04:00:00,Mon,17534,750 2004-01-06,00:00:00,01:00:00,Tue,17262,747 2004-01-06,01:00:00,02:00:00,Tue,19072,777 2004-01-06,02:00:00,03:00:00,Tue,18275,785 I want to use column 2:startTime and 5:count and I want to group by column day and sum the counts in respective hours. code: Does not give the output import numpy as np