Question

维护人员注意：这个问题已经过时，因为多年前已经弃用并删除了bokeh.charts API。但请参阅下面的答案，了解如何在较新版本的Bokeh中使用稳定的bokeh.plotting API创建分组条形图

我想创建一个简单的条形图（如官方示例页面中的那个）

中执行代码

但它显示错误：

---------------------------------------------------------------------------
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

官方的例子确实有用

网址：http://bokeh.pydata.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)

但是，我不想使用pandas，我想使用这样一个简单的python字典：

my_simple_dict = {
    'Group 1': [22,33,44,55],
    'Group 2': [44,66,0,24],
    'Group 3': [2,99,33,51]
}

我是否无法获得显示树组（第1组，第2组，第3组）的条形图，其中x轴从1到4？

注意：我正在使用python 2.7

Answer 1

问题和其他答案已经过时，因为bokeh.charts几年前已被弃用和删除。然而。自那时起，使用稳定的bokeh.plotting API对分组和堆积条形图的支持有了很大改进：

https://bokeh.pydata.org/en/latest/docs/user_guide/categorical.html

以下是一个完整的例子：

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

目前我找到的解决方案是改变字典结构

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)

如果有人知道更好的方法，请告诉我

散景 - 分组条形图

2 个答案: