Bokeh - Grouped Bar chart

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Maintainer note: This question as-is is obsolete, since the bokeh.charts API was deprecated and removed years ago.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/basic/bars.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), 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