在Bokeh中将“字符串”类型转换为“ int”时，无法正确绘制图形

Question

i am fetching some attribute values from xml , which are numeric in nature but coming as type 'string'

i am converting those 'strings' type to 'int' , and trying to plot a Bar graph in Bokeh. The graph is not populating correctly (attached) . Any suggestion ?

Below is the code

import pandas as pd
from bokeh.charts import Bar, output_file, show
#String values fetched from xml
var='5'
var1='6'
#Converting string to int
var=int(var)
var1=int(var1)

#Creating a dataframe
d = {'col1': [var], 'col2': [var1]}
df=pd.DataFrame(data=d)
print df

#Output
#   col1  col2
#0     0     4

#Displaying with Bokeh

p=Bar(df)
output_file("bar.html")
show(p)

Answer 1

First off: Bar is part of the old, deprecated bokeh.charts API that has since been completely removed from core Bokeh. It is still available as the bkcharts package, but it is completely unmaintained and unsupported . It should not be used for any new work at this point.

---

However, recent work greatly improved the support for bar and other categorical plots using the stable, supported bokeh.plotting API. There is large new User's Guide Section purely dedicated to explaining and demonstrating many kind of bar charts, both simple and sophisticated. Moreover, now that bar plots are easy to make using standard bokeh.plotting calls, the general guidance and documentation for hover tools now applies as well.

It's not quite clear to me from your example code what you are trying to accomplish. Here is a very stripped down version of something that might be similar:

from bokeh.io import output_file, show
from bokeh.plotting import figure

p = figure(x_range=['col1', 'col2'])
p.vbar(x=['col1', 'col2'], top=[5, 6], width=0.8)

output_file("bar.html")
show(p)

That code produces this output:

Here is a more complete example of a simple bar chart using pandas statistics (similar to what Bar would do) with hover tool using the "cars" sample data and the bokeh.plotting API:

from bokeh.io import show, output_file
from bokeh.models import HoverTool
from bokeh.plotting import figure
from bokeh.sampledata.autompg import autompg as df

output_file("groupby.html")

df.cyl = df.cyl.astype(str)
group = df.groupby('cyl')

p = figure(plot_height=350, x_range=group, toolbar_location=None, tools="")
p.vbar(x='cyl', top='mpg_mean', width=0.9, source=group)

p.add_tools(HoverTool(tooltips=[("Avg MPG", "@mpg_mean")]))

show(p)

Which produces the following result