bokeh - ValueError: Keyword argument sequences

bokeh - ValueError: Keyword argument sequences

下面是两组代码。第一组代码有效并给出了预期的结果。但是,当我尝试扩展数据帧的大小时,如在第二组代码中那样,使用额外的列,我收到一条错误消息。

我收到的错误消息如下。

raise ValueError("Keyword argument sequences for broadcasting must all be the same lengths. Got lengths: %r" % sorted(list(lengths)))

ValueError: Keyword argument sequences for broadcasting must all be the same lengths. Got lengths: [3, 4]

raise ValueError("Keyword argument sequences for broadcasting must all be the same lengths. Got lengths: %r" % sorted(list(lengths)))

ValueError: Keyword argument sequences for broadcasting must all be the same lengths. Got lengths: [3, 4]

有效的代码 1

import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, show
from bokeh.palettes import Spectral3

df = pd.DataFrame({'Category': ['<£5000', '£100K to £250K'],
           '01/01/2014': [8,1],
           '01/01/2015': [8,2],
           '01/01/2016': [7,1]})


grouped = df.groupby('Category')['01/01/2014', '01/01/2015', '01/01/2016'].mean().round(0)

source = ColumnDataSource(grouped)
countries = source.data['Category'].tolist()
p = figure(x_range=countries)

p.vbar_stack(stackers=['01/01/2014', '01/01/2015', '01/01/2016'],
     x='Category', source=source,
     legend = ['01/01/2014 ', '01/01/2015 ', '01/01/2016 '],
     width=0.5, color=Spectral3)


p.title.text ='Average Number of Trades by Portfolio Size'
p.legend.location = 'top_right'

p.xaxis.axis_label = 'Portfolio Size'
p.xgrid.grid_line_color = None  #remove the x grid lines

p.yaxis.axis_label = 'Average Number of Trades'

show(p)

代码 2 无效。添加的其他日期。

import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, show
from bokeh.palettes import Spectral3

df = pd.DataFrame({'Category': ['<£5000', '£100K to £250K'],
           '01/01/2014': [8,1],
           '01/01/2015': [8,2],
           '01/01/2016': [7,1],
           '01/01/2017': [9,4]})


grouped = df.groupby('Category')['01/01/2014', '01/01/2015', '01/01/2016', '01/01/2017'].mean().round(0)

source = ColumnDataSource(grouped)
countries = source.data['Category'].tolist()
p = figure(x_range=countries)

p.vbar_stack(stackers=['01/01/2014', '01/01/2015', '01/01/2016', '01/01/2017'],
     x='Category', source=source,
     legend = ['01/01/2014 ', '01/01/2015 ', '01/01/2016 ', '01/01/2017 '],
     width=0.5, color=Spectral3)


p.title.text ='Average Number of Trades by Portfolio Size'
p.legend.location = 'top_right'

p.xaxis.axis_label = 'Portfolio Size'
p.xgrid.grid_line_color = None  #remove the x grid lines

p.yaxis.axis_label = 'Average Number of Trades'

show(p)

问题是您增加了数据框中的列数,但颜色集 Spectral3 仍然只有 3 种颜色。 以下代码使用 Spectral[11],因此适用于最多 11 个数据帧列。对于更多列/颜色,您需要切换到提供更多颜色的其他调色板(针对 Bokeh v1.0.4 测试的代码)

import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, show
from bokeh.palettes import Spectral

df = pd.DataFrame({ 'Category': ['<5000 EUR', '100K EUR to 250K EUR'],
                    '01/01/2014': [8, 1],
                    '01/01/2015': [8, 2],
                    '01/01/2016': [7, 1],
                    '01/01/2017': [9, 4] })

nmb_columns = (len(df.columns) - 1)
grouped = df.groupby('Category')['01/01/2014', '01/01/2015', '01/01/2016', '01/01/2017'].mean().round(0)

source = ColumnDataSource(grouped)
countries = source.data['Category'].tolist()
p = figure(x_range = countries)

p.vbar_stack(stackers = ['01/01/2014', '01/01/2015', '01/01/2016', '01/01/2017'],
     x = 'Category', source = source,
     legend = ['01/01/2014 ', '01/01/2015 ', '01/01/2016 ', '01/01/2017 '],
     width = 0.5, color = Spectral[11][:nmb_columns])

p.title.text = 'Average Number of Trades by Portfolio Size'
p.legend.location = 'top_left'
p.legend.click_policy = 'hide'

p.xaxis.axis_label = 'Portfolio Size'
p.xgrid.grid_line_color = None  # remove the x grid lines

p.yaxis.axis_label = 'Average Number of Trades'

show(p)

结果: