UPDATE: The answer below is still correct in all major points, but the API has changed slightly to be more explicit as of Bokeh 0.7. In general, things like:
rect(...)
should be replaced with
p = figure(...)
p.rect(...)
Here are the relevant lines from the Les Mis examples, simplified to your case. Let's take a look:
# A "ColumnDataSource" is like a dict, it maps names to columns of data.
# These names are not special we can call the columns whatever we like.
source = ColumnDataSource(
data=dict(
x = [row['name'] for row in joined],
y = [row['name'] for row in joined],
color = list_of_colors_one_for_each_row,
)
)
# We need a list of the categorical coordinates
names = list(set(row['name'] for row in joined))
# rect takes center coords (x,y) and width and height. We will draw
# one rectangle for each row.
rect('x', 'y', # use the 'x' and 'y' fields from the data source
0.9, 0.9, # use 0.9 for both width and height of each rectangle
color = 'color', # use the 'color' field to set the color
source = source, # use the data source we created above
x_range = names, # sequence of categorical coords for x-axis
y_range = names, # sequence of categorical coords for y-axis
)
A few notes:
For numeric data x_range and y_range usually get supplied automatically. We have to give them explicitly here because we are using categorial coordinates.
You can order the list of names for x_range and y_range however you like, this is the order they are displayed on the plot axis.
I'm assuming you want to use categorical coordinates. :) This is what the Les Mes example does. See the bottom of this answer if you want numerical coordinates.
Also, the Les Mis example was a little more complicated (it had a hover tool) which is why we created a ColumnDataSource by hand. If you just need a simple plot you can probably skip creating a data source yourself, and just pass the data in to rect directly:
names = list(set(row['name'] for row in joined))
rect(names, # x (categorical) coordinate for each rectangle
names, # y (categorical) coordinate for each rectangle
0.9, 0.9, # use 0.9 for both width and height of each rectangle
color = some_colors, # color for each rect
x_range = names, # sequence of categorical coords for x-axis
y_range = names, # sequence of categorical coords for y-axis
)
Another note: this only plots rectangles on the diagonal, where the x- and y-coordinates are the same. That seems to be what you want from your description. But just for completeness, it's possible to plot rectangles that have different x- and y-coordinates. The Les Mis example does this.
Finally, maybe you don't actually want categorical axes? If you just want to use the numeric index of the coordinates, its even simpler:
inds = [row['index'] for row in joined]
rect(inds, # x-coordinate for each rectangle
inds, # y-coordinate for each rectangle
0.9, 0.9, # use 0.9 for both width and height of each rectangle
color = some_colors, # color for each rect
)
Edit: Here is a complete runnable example that uses numeric coords:
from bokeh.plotting import *
output_file("foo.html")
inds = [2, 5, 6, 8, 9]
colors = ["red", "orange", "blue", "green", "#4488aa"]
rect(inds, inds, 1.0, 1.0, color=colors)
show()
and here is one that uses the same values as categorical coords:
from bokeh.plotting import *
output_file("foo.html")
inds = [str(x) for x in [2, 5, 6, 8, 9]]
colors = ["red", "orange", "blue", "green", "#4488aa"]
rect(inds, inds, 1.0, 1.0, color=colors, x_range=inds, y_range=inds)
show()
