Bokeh - Grouped Bar chart - python-2.7

Question

Maintainer note: This question as-is is obsolete, since the bokeh.charts API was deprecated and removed years ago. But see the answer below for how to create grouped bar charts with the stable bokeh.plotting API in newer versions of Bokeh
I want to create a simple bar chart (like the one in the oficial example page)
I tried executing the code in this old answer Plotting Bar Charts with Bokeh
but it show the error:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-2-ba53ce344126> in <module>()
11
12 bar = Bar(xyvalues, cat, title="Stacked bars",
---> 13 xlabel="category", ylabel="language")
14
15 output_file("stacked_bar.html")
/usr/local/lib/python2.7/dist-packages/bokeh/charts/builders/bar_builder.pyc in Bar(data, label, values, color, stack, group, agg, xscale, yscale, xgrid, ygrid, continuous_range, **kw)
318 kw['y_range'] = y_range
319
--> 320 chart = create_and_build(BarBuilder, data, **kw)
321
322 # hide x labels if there is a single value, implying stacking only
/usr/local/lib/python2.7/dist-packages/bokeh/charts/builder.pyc in create_and_build(builder_class, *data, **kws)
60 # create the new builder
61 builder_kws = {k: v for k, v in kws.items() if k in builder_props}
---> 62 builder = builder_class(*data, **builder_kws)
63
64 # create a chart to return, since there isn't one already
/usr/local/lib/python2.7/dist-packages/bokeh/charts/builder.pyc in __init__(self, *args, **kws)
280
281 # handle input attrs and ensure attrs have access to data
--> 282 attributes = self._setup_attrs(data, kws)
283
284 # remove inputs handled by dimensions and chart attributes
/usr/local/lib/python2.7/dist-packages/bokeh/charts/builder.pyc in _setup_attrs(self, data, kws)
331 attributes[attr_name].iterable = custom_palette
332
--> 333 attributes[attr_name].setup(data=source, columns=attr)
334
335 else:
/usr/local/lib/python2.7/dist-packages/bokeh/charts/attributes.pyc in setup(self, data, columns)
193
194 if columns is not None and self.data is not None:
--> 195 self.set_columns(columns)
196
197 if self.columns is not None and self.data is not None:
/usr/local/lib/python2.7/dist-packages/bokeh/charts/attributes.pyc in set_columns(self, columns)
185 # assume this is now the iterable at this point
186 self.iterable = columns
--> 187 self._setup_default()
188
189 def setup(self, data=None, columns=None):
/usr/local/lib/python2.7/dist-packages/bokeh/charts/attributes.pyc in _setup_default(self)
142 def _setup_default(self):
143 """Stores the first value of iterable into `default` property."""
--> 144 self.default = next(self._setup_iterable())
145
146 def _setup_iterable(self):
/usr/local/lib/python2.7/dist-packages/bokeh/charts/attributes.pyc in _setup_iterable(self)
320
321 def _setup_iterable(self):
--> 322 return iter(self.items)
323
324 def get_levels(self, columns):
TypeError: 'NoneType' object is not iterable
The oficial example did work
URL: http://docs.bokeh.org/en/0.11.0/docs/user_guide/charts.html#userguide-charts-data-types
from bokeh.charts import Bar, output_file, show
from bokeh.sampledata.autompg import autompg as df
p = Bar(df, label='yr', values='mpg', agg='median', group='origin',
title="Median MPG by YR, grouped by ORIGIN", legend='top_right')
output_file("bar.html")
show(p)
BUT, I don't want to use pandas, I want to use a simple python dictionary like this:
my_simple_dict = {
'Group 1': [22,33,44,55],
'Group 2': [44,66,0,24],
'Group 3': [2,99,33,51]
}
How cant I achive a Bar chart that shows the tree groups (Group 1, Group 2, Group 3) with the x-axis going from 1 to 4?
NOTE: I am working with python 2.7

Answer 1

The question and other answers are obsolete, as bokeh.charts was deprecated and removed several years ago. However. support for grouped and stacked bar charts using the stable bokeh.plotting API has improved greatly since then:
https://docs.bokeh.org/en/latest/docs/user_guide/categorical.html
Here is a full example:
from bokeh.io import show
from bokeh.models import ColumnDataSource, FactorRange
from bokeh.plotting import figure
fruits = ['Apples', 'Pears', 'Nectarines', 'Plums', 'Grapes', 'Strawberries']
years = ['2015', '2016', '2017']
data = {'fruits' : fruits,
'2015' : [2, 1, 4, 3, 2, 4],
'2016' : [5, 3, 3, 2, 4, 6],
'2017' : [3, 2, 4, 4, 5, 3]}
# this creates [ ("Apples", "2015"), ("Apples", "2016"), ("Apples", "2017"), ("Pears", "2015), ... ]
x = [ (fruit, year) for fruit in fruits for year in years ]
counts = sum(zip(data['2015'], data['2016'], data['2017']), ()) # like an hstack
source = ColumnDataSource(data=dict(x=x, counts=counts))
p = figure(x_range=FactorRange(*x), plot_height=250, title="Fruit Counts by Year",
toolbar_location=None, tools="")
p.vbar(x='x', top='counts', width=0.9, source=source)
p.y_range.start = 0
p.x_range.range_padding = 0.1
p.xaxis.major_label_orientation = 1
p.xgrid.grid_line_color = None
show(p)

Answer 2

For now the solution I found is changing the dict structure
from bokeh.charts import Bar, output_file, show, hplot
import pandas as pd
my_simple_dict = {
'Group 1': [22,33,44,55],
'Group 2': [44,66,0,24],
'Group 3': [2,99,33,51]
}
my_data_transformed_dict = {}
my_data_transformed_dict['x-axis'] = []
my_data_transformed_dict['value'] = []
my_data_transformed_dict['group-name'] = []
for group, group_list in my_simple_dict.iteritems():
x_axis = 0
for item in group_list:
x_axis += 1
my_data_transformed_dict['x-axis'].append(x_axis)
my_data_transformed_dict['value'].append(item)
my_data_transformed_dict['group-name'].append(group)
my_bar = Bar(my_data_transformed_dict, values='value',label='x-axis',group='group-name',legend='top_right')
output_file("grouped_bar.html")
show(my_bar)
If someone knows a better way please tell me