Styjun

I have generated a simple bar chart. In order to make it more interactive, I have added Hovertool into the graph.

from bokeh.io import show, output_notebook
from bokeh.plotting import figure, output_file
from bokeh.models.glyphs import HBar
from bokeh.models import ColumnDataSource, Legend, HoverTool
output_notebook()

# Set x and y
functions = ['func_1', 'func_2', 'func_3']
percentage = [233.14, 312.03, 234.00]

# Set data source (color needs to be set precisely with len(category))
source = ColumnDataSource(data=dict(functions=functions, percentage=percentage))

# Set the x_range to the list of categories above
p = figure(x_range=functions, plot_height=600, plot_width=800, title="The Overall Use of my functions",
 x_axis_label='Functions', y_axis_label='Percentage')

# Categorical values can also be used as coordinates
p.vbar(x='functions', top='percentage', width=0.9, source=source)
p.add_tools(HoverTool(tooltips=[('Percentage', "@percentage")]))

show(p)

Although it shows a value from y axis correctly, I would like to display a label from x axis instead (e.g., Func1: 9.45). Just like the picture that is shown from the link (I cannot post an image yet):

https://i.ibb.co/235jR39/Untitled.png

Update#1
I tried to come up with something, this is what I got:

# Set Hover
percentage = list(map(lambda i: str(i), percentage))
my_hover = list(zip(functions, percentage))
p.add_tools(HoverTool(tooltips=my_hover))

It turns out it shows every detail in every bar as shown below

https://i.ibb.co/72hmD8q/Untitled-2.png

This code works for Bokeh v1.0.4.

import math
import numpy as np
import pandas as pd
from bokeh.models import ColumnDataSource, HoverTool
from bokeh.plotting import figure, show
from bokeh.palettes import Category10

df = pd.DataFrame(data = np.random.rand(10, 1), columns = ['percentage'], index = ['Func '.format(nmb) for nmb in range(10)])
df['color'] = Category10[10]

source = ColumnDataSource(data = dict(functions = df.index.values, percentage = df['percentage'].values, color = df['color'].values))

p = figure(x_range = df.index.values, plot_height = 600, plot_width = 800, title = "The Overall Use of my functions",
 x_axis_label = 'functions', y_axis_label = 'percentage')

p.vbar(x = 'functions', top = 'percentage', width = 0.9, color = 'color', source = source)
p.add_tools(HoverTool(tooltips = '<font color=blue>@functions:</font><font color=red> @percentage</font>'))

p.xgrid.grid_line_color = None
p.xaxis.major_label_orientation = math.pi / 4 # Rotate axis' labels

show(p)

Result: