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bokeh - ValueError: Keyword argument sequences
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Below is two sets of code. The first set of code works and gives the desired outcome. However, when i try to extend the size of the dataframe, as in the second set of code, with an additional column i get an error message.
The error message I get is below.
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]
Code 1 which works
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)
Code 2 which does not work. Additional date added in.
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)
pandas bokeh stacked-chart
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
add a comment |
Below is two sets of code. The first set of code works and gives the desired outcome. However, when i try to extend the size of the dataframe, as in the second set of code, with an additional column i get an error message.
The error message I get is below.
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]
Code 1 which works
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)
Code 2 which does not work. Additional date added in.
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)
pandas bokeh stacked-chart
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
add a comment |
Below is two sets of code. The first set of code works and gives the desired outcome. However, when i try to extend the size of the dataframe, as in the second set of code, with an additional column i get an error message.
The error message I get is below.
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]
Code 1 which works
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)
Code 2 which does not work. Additional date added in.
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)
pandas bokeh stacked-chart
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
Below is two sets of code. The first set of code works and gives the desired outcome. However, when i try to extend the size of the dataframe, as in the second set of code, with an additional column i get an error message.
The error message I get is below.
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]
Code 1 which works
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)
Code 2 which does not work. Additional date added in.
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)
pandas bokeh stacked-chart
pandas bokeh stacked-chart
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
asked Mar 27 at 21:15
ben121ben121
3761 silver badge13 bronze badges
3761 silver badge13 bronze badges
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
The problem is that you increased the number of column in your dataframe but the color set Spectral3 has still only 3 colors.
The following code uses Spectral[11] so it is good for up to 11 dataframe columns. For more column / colors you would need to switch to other palette offering more colors (code tested for Bokeh v1.0.4)
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)
Result:
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
Brilliant thank you.
– ben121
Mar 28 at 6:57
add a comment |
Your Answer
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
The problem is that you increased the number of column in your dataframe but the color set Spectral3 has still only 3 colors.
The following code uses Spectral[11] so it is good for up to 11 dataframe columns. For more column / colors you would need to switch to other palette offering more colors (code tested for Bokeh v1.0.4)
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)
Result:
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
Brilliant thank you.
– ben121
Mar 28 at 6:57
add a comment |
The problem is that you increased the number of column in your dataframe but the color set Spectral3 has still only 3 colors.
The following code uses Spectral[11] so it is good for up to 11 dataframe columns. For more column / colors you would need to switch to other palette offering more colors (code tested for Bokeh v1.0.4)
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)
Result:
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
Brilliant thank you.
– ben121
Mar 28 at 6:57
add a comment |
The problem is that you increased the number of column in your dataframe but the color set Spectral3 has still only 3 colors.
The following code uses Spectral[11] so it is good for up to 11 dataframe columns. For more column / colors you would need to switch to other palette offering more colors (code tested for Bokeh v1.0.4)
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)
Result:
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
The problem is that you increased the number of column in your dataframe but the color set Spectral3 has still only 3 colors.
The following code uses Spectral[11] so it is good for up to 11 dataframe columns. For more column / colors you would need to switch to other palette offering more colors (code tested for Bokeh v1.0.4)
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)
Result:
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
answered Mar 27 at 22:18
TonyTony
2,9791 gold badge5 silver badges23 bronze badges
2,9791 gold badge5 silver badges23 bronze badges
Brilliant thank you.
– ben121
Mar 28 at 6:57
add a comment |
Brilliant thank you.
– ben121
Mar 28 at 6:57
Brilliant thank you.
– ben121
Mar 28 at 6:57
Brilliant thank you.
– ben121
Mar 28 at 6:57
add a comment |
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