使用散景创建条形图

Question

there is an example on the bokeh website:

https://docs.bokeh.org/en/latest/docs/gallery/bar_nested.html

but it does not work on my Jupiter notebook.

I have the following data frame:

                precision   recall  f1
Random Forest   0.493759    1.0     0.661096
XGBoost         0.493759    1.0     0.661096

I want to build a graph that compares the two models on these 3 metrics. But to start, I just wanted to compare one metric. this is my non-working code:

from bokeh.io import show, output_file
from bokeh.models import ColumnDataSource, FactorRange
from bokeh.plotting import figure

data = pd.DataFrame({'precision':[percision_rf,percision_xgb],'recall':[recall_rf,recall_xgb],'f1':[f1_rf,f1_xgb]})
data.rename({0:'Random Forest',1:'XGBoost'}, inplace=True)

source = ColumnDataSource(data=data)

p = figure()

p.vbar(x='Random Forest', top=0.9, 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) 

There is an example of a simple bar graph on the bokeh website, but it is not using a ColumnDataSource.

Answer 1

When you pass a DataFrame to a ColumnDataSource , Bokeh makes CDS columns out of the columns of the DataFrame. Those are what you can refer to in the glyph methods, and then the glyph will draw glyphs for all values of that column. For example, in the example above, you could do

# plot bars for every precision value along the x axis
p.vbar(x='precision', top=0.9, width=0.9, source=source)

All Bokeh glyphs are inherently "vectorized" in this way.

In the above code, x='Random Forest' is not meaningful to pass to vbar , because there is no column in the DataFrame (and hence no column in the CDS) called "Random Forest".