Maybe this can help you:
import pandas as pd
from bokeh.layouts import row, widgetbox
from bokeh.models import Select, HoverTool, ColumnDataSource
from bokeh.palettes import Spectral5
from bokeh.plotting import curdoc, figure
from bokeh.sampledata.autompg import autompg as df
from bokeh.io import show
df = df.copy()
SIZES = list(range(6, 22, 3))
COLORS = Spectral5
N_SIZES = len(SIZES)
N_COLORS = len(COLORS)
df.cyl = df.cyl.astype(str)
df.yr = df.yr.astype(str)
del df[‘name’]
columns = sorted(df.columns)
discrete = [x for x in columns if df.dtype == object]
continuous = [x for x in columns if x not in discrete]
def create_figure():
xs = df[x.value].values
ys = df[y.value].values
x_title = x.value.title()
y_title = y.value.title()
kw = dict()
if x.value in discrete:
kw['x_range'] = sorted(set(xs))
if y.value in discrete:
kw['y_range'] = sorted(set(ys))
kw['title'] = "%s vs %s" % (x_title, y_title)
p = figure(plot_height = 600, plot_width = 800, tools = 'pan,box_zoom,wheel_zoom,reset', **kw)
p.xaxis.axis_label = x_title
p.yaxis.axis_label = y_title
if x.value in discrete:
p.xaxis.major_label_orientation = pd.np.pi / 4
sz = 9
if size.value != 'None':
if len(set(df[size.value])) > N_SIZES:
groups = pd.qcut(df[size.value].values, N_SIZES, duplicates = 'drop')
else:
groups = pd.Categorical(df[size.value])
sz = [SIZES[xx] for xx in groups.codes]
c = "#31AADE"
if color.value != 'None':
if len(set(df[color.value])) > N_SIZES:
groups = pd.qcut(df[color.value].values, N_COLORS, duplicates = 'drop')
else:
groups = pd.Categorical(df[color.value])
c = [COLORS[xx] for xx in groups.codes]
source = ColumnDataSource(dict(mpg = xs, hp = ys))
p.circle(x = 'mpg', y = 'hp', color = c, size = sz, line_color = "white", alpha = 0.6, hover_color = 'white', hover_alpha = 0.5, source = source)
p.add_tools(HoverTool(tooltips = [ ("Mpg", "@mpg"), ("Hp", "@hp") ]))
return p
def update(attr, old, new):
layout.children[1] = create_figure()
x = Select(title = ‘X-Axis’, value = ‘mpg’, options = columns)
x.on_change(‘value’, update)
y = Select(title = ‘Y-Axis’, value = ‘hp’, options = columns)
y.on_change(‘value’, update)
size = Select(title = ‘Size’, value = ‘None’, options = [‘None’] + continuous)
size.on_change(‘value’, update)
color = Select(title = ‘Color’, value = ‘None’, options = [‘None’] + continuous)
color.on_change(‘value’, update)
controls = widgetbox([x, y, color, size], width = 200)
layout = row(controls, create_figure())
curdoc().add_root(layout)
curdoc().title = “Crossfilter”
show(layout)
``
···
On Wednesday, November 21, 2018 at 3:36:24 PM UTC+1, Raha Asadimehr wrote:
Hello ,
I try to use this example :
but I could not able to add hover tool for each point .
Could you please give me some help ?
from bokeh.layouts import row, widgetbox
from bokeh.models import Select
from bokeh.palettes import Spectral5
from bokeh.plotting import curdoc, figure
from bokeh.sampledata.autompg import autompg_clean as df3
from bokeh.models import LinearInterpolator, HoverTool,ColumnDataSource
import numpy as np
df = df1.copy()
df=df.rename( columns={“sum”: “n”})
df[‘l1’]= pd.Categorical(df[‘l’], categories=df[‘l’].unique()).codes
df[‘aa_type’]= pd.Categorical(df[‘aa’], categories=df[‘aa’].unique()).codes
df[‘uu_type’]= pd.Categorical(df[‘uu’], categories=df[‘uu’].unique()).codes
df[‘n_range’]= df.n_code.values*5
SIZES = list(set(df.n_range.values))
N_SIZES = len(SIZES)
COLORS =Spectral5
N_COLORS = len(COLORS)
aa= list(set(df.aa.values))
N_aa = len(aa)
uu = list(set(df.uu.values))
N_uu= len(uu)
columns = sorted(df.columns)
discrete = [x for x in columns if df.dtype == object]
continuous = [x for x in columns if x not in discrete]
def create_figure():
xs = df[x.value].values
ys = df[y.value].values
x_title = x.value.title()
y_title = y.value.title()
kw = dict()
if x.value in discrete:
kw[‘x_range’] = sorted(set(xs))
if y.value in discrete:
kw[‘y_range’] = sorted(set(ys))
kw[‘title’] = “%s vs %s” % (x_title, y_title)
source= ColumnDataSource(data=dict(xs=, ys=,RName=, PName=, n=, A=))
new_data = dict(
x=xs,
y=ys,
R=df[‘RName’],
P=df[‘PName’],
N=df[‘n’],
A=df[‘A’],
)
source.data=new_data
hover = HoverTool(tooltips=[ (“R”, “@RName”), (“P”, “@PName”), (“N”, “@n”) , (“A”, “@A”) ])
p = figure(plot_height=800, plot_width=800, tools=‘pan,box_zoom,reset’, **kw)
p.add_tools(hover)
p.xaxis.axis_label = x_title
p.yaxis.axis_label = y_title
if x.value in discrete:
p.xaxis.major_label_orientation = pd.np.pi / 4
sz = 20
if size.value != ‘None’:
if len(set(df[size.value])) > N_SIZES:
groups = pd.qcut(df[size.value].values, N_SIZES, duplicates=‘drop’)
else:
groups = pd.Categorical(df[size.value])
sz = [SIZES[xx] for xx in groups.codes]
c = “#31AADE”
if color.value != ‘None’:
if len(set(df[color.value])) > N_SIZES:
groups = pd.qcut(df[color.value].values, N_COLORS, duplicates=‘drop’)
else:
groups = pd.Categorical(df[color.value])
c = [COLORS[xx] for xx in groups.codes]
a = “I”
if aa.value != ‘All’:
if len(set(df[aa.value])) > N_ASSET:
groups = pd.qcut(df[aa.value].values,N_aa, duplicates=‘drop’)
else:
groups = pd.Categorical(df[aa.value])
a = [aa[xx] for xx in groups.codes]
u = “InterestRate:CrossCurrency:Basis”
if uu.value != ‘All’:
if len(set(df[uu.value])) > N_uu:
groups = pd.qcut(df[uu.value].values,N_uu, duplicates=‘drop’)
else:
groups = pd.Categorical(df[uu.value])
u= [uu[xx] for xx in groups.codes]
p.circle(x=xs, y=ys, color=c, size=sz, line_color=“white”, alpha=0.6, hover_color=‘white’, hover_alpha=0.5)
#,source=source
return p
def update(attr, old, new):
layout.children[1] = create_figure()
x = Select(title=‘X-Axis’, value=‘uu_type’, options=columns)
x.on_change(‘value’, update)
y = Select(title=‘Y-Axis’, value=‘location’, options=columns)
y.on_change(‘value’, update)
asset= Select(title=“aa”, value=“All”, options=list(set(df1.aa.values)))
asset.on_change(‘value’, update)
upi= Select(title=“uu”, value=“All”, options=list(set(df1.uu.values)))
upi.on_change(‘value’, update)
size = Select(title=‘Size’, value=‘n_range’, options=[‘None’] + continuous)
size.on_change(‘value’, update)
color = Select(title=‘Color’, value=‘aa_type’, options=[‘None’] + continuous)
color.on_change(‘value’, update)
controls = widgetbox([x, y, color, size,aa,uu], width=550)
layout = row(controls, create_figure())
curdoc().add_root(layout)
curdoc().title = …
``