سلام ،
من سعی می کنم از این مثال استفاده کنم:

https://demo.bokehplots.com/ apps / crossfilter

اما من نمیتوانستم برای اضافه کردن یک ابزار شناور برای هر نقطه اضافه کنم.

آیا می توانید لطفا به من کمک کنید؟

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 = …

``