Why only the first rect has hover and how to change the text style?

firstly: this is my update code:

def update(attrname,old,new):

plot.xaxis.axis_label=x_axis.value

plot.yaxis.axis_label=‘numbers’

source.data=dict(

x=axis_map[x_axis.value],

y=height_map[x_axis.value],

height=height_map[x_axis.value]*2.0

)

plot.x_range.factors=axis_map[x_axis.value]

plot.rect(x=axis_map[x_axis.value],y=height_map[x_axis.value],height=height_map[x_axis.value]*2.0)

after updating only the first bar shows its hover while the other bars don’t :

secondly: you may see the x_axis name above, they are too long to show correctly, how can I change them to an angle so to show correctly like bar chart’s x_axis

many thanks

I’ve solved the second problem by changing its orientation,.

在 2016年6月5日星期日 UTC+8下午3:40:09,Qiwei Peng写道:

···

firstly: this is my update code:

def update(attrname,old,new):

plot.xaxis.axis_label=x_axis.value

plot.yaxis.axis_label=‘numbers’

source.data=dict(

x=axis_map[x_axis.value],

y=height_map[x_axis.value],

height=height_map[x_axis.value]*2.0

)

plot.x_range.factors=axis_map[x_axis.value]

plot.rect(x=axis_map[x_axis.value],y=height_map[x_axis.value],height=height_map[x_axis.value]*2.0)

after updating only the first bar shows its hover while the other bars don’t :

secondly: you may see the x_axis name above, they are too long to show correctly, how can I change them to an angle so to show correctly like bar chart’s x_axis

many thanks

Please provide a complete code sample. That is, one that someone could immediately run without modification, to see the problem. I can’t speculate about what the issue might be without running the code, and I can’t run it if it is not a complete script. Also FYI I am technically on vacation so any response from me will probably be at least a few days away.

Bryan

···

On Jun 5, 2016, at 02:40, Qiwei Peng [email protected]mail.com wrote:

firstly: this is my update code:

def update(attrname,old,new):

plot.xaxis.axis_label=x_axis.value

plot.yaxis.axis_label=‘numbers’

source.data=dict(

x=axis_map[x_axis.value],

y=height_map[x_axis.value],

height=height_map[x_axis.value]*2.0

)

plot.x_range.factors=axis_map[x_axis.value]

plot.rect(x=axis_map[x_axis.value],y=height_map[x_axis.value],height=height_map[x_axis.value]*2.0)

after updating only the first bar shows its hover while the other bars don’t :

secondly: you may see the x_axis name above, they are too long to show correctly, how can I change them to an angle so to show correctly like bar chart’s x_axis

many thanks

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from os.path import dirname, join

#import numpy as np

import pandas.io.sql as psql

import sqlite3 as sql

import pandas as pd

from pandas import DataFrame

import numpy as np

from pandas.util.testing import assert_frame_equal

from bokeh.client import push_session

from bokeh.plotting import figure,output_file,show

from bokeh.charts import Bar,Area,Line

from bokeh.models import ColumnDataSource, HoverTool, HBox, VBoxForm,CustomJS,VBox

from bokeh.models.widgets import Slider, Select, TextInput

from bokeh.io import curdoc,vform

#whole_data read

data_all=pd.read_table(‘results/newresults’,sep=’ \t’,names=[‘name’,‘company’,‘industry’,‘location’])

#three

local_counts=data_all[‘location’].value_counts()

industry_counts=data_all[‘industry’].value_counts()

company_counts=data_all[‘company’].value_counts()

local_counts.to_csv(‘out3.csv’,sep=’,’)

industry_counts.to_csv(‘out4.csv’,sep=’,’)

company_counts.to_csv(‘out5.csv’,sep=’,’)

industry_counts1=pd.read_csv(‘out4.csv’,names=[‘industry’,‘numbers’],sep=’,’)

local_counts1=pd.read_csv(‘out3.csv’,names=[‘location’,‘numbers’],sep=’,’)

company_counts1=pd.read_csv(‘out5.csv’,names=[‘company’,‘numbers’],sep=’,’)

test=industry_counts1[‘industry’]

a=test.values

test.to_csv(‘outout.csv’,sep=’,’)

test1=pd.read_csv(‘outout.csv’)

test1=test1.T

#test1.to_csv(‘new.csv’)

#f=open(‘finaltest/output.txt’,‘w’)

#f.write(str(a))

#f.close()

#zimu=[‘a’,‘b’,‘c’,‘d’,‘e’,‘f’,‘h’,‘i’,‘j’,‘k’]

#b=np.loadtxt(‘new.csv’,str,delimiter=’,’)

#print b

a=company_counts1[‘company’].values

np.savetxt(‘here2.csv’,a,fmt=’%s’)

company=np.loadtxt(‘here2.csv’,str,delimiter=’\n’)

company=list(company)

b=local_counts1[‘location’].values

np.savetxt(‘here3.csv’,b,fmt=’%s’)

location=np.loadtxt(‘here3.csv’,str,delimiter=’\n’)

location=list(location)

c=industry_counts1[‘industry’].values

np.savetxt(‘here4.csv’,c,fmt=’%s’)

industry=np.loadtxt(‘here4.csv’,str,delimiter=’\n’)

industry=list(industry)

#industry=[‘Computer Software’,‘Information Technology and Services’,‘Research’,‘Financial Services’,‘Chemicals’,‘Biotechnology’,‘Higher Education’,‘Electrical/Electronic Manufacturing’,‘Pharmaceuticals’,‘Telecommunications’]

#location=[‘Chengdu, Sichuan, China’,‘China’,‘Beijing City, China’,‘Shanghai City, China’,‘Shenzhen, Guangdong, China’,‘Greater New York City Area’,‘San Francisco Bay Area’,‘Canada’,‘Shanghai Suburb, China’,‘Greater Boston Area’]

#company=[‘Sichuan University’,‘Intel’,‘Huawei’,‘IBM’,‘Tencent’,‘Apple’,‘Google’,‘Microsoft’,‘EMC’,‘Motorola Solutions’]

indus_height=industry_counts1[‘numbers’][:10]

y_indus_height=indus_height/2.0

local_height=local_counts1[‘numbers’][:10]

y_local_height=local_height/2.0

company_height=company_counts1[‘numbers’][:10]

y_company_height=company_height/2.0

hover=HoverTool(tooltips=[

("type","@x"),

("number","@height")

])

output_file(‘tot.html’)

indus_counts_array=industry_counts1[‘numbers’].values

indus_counts_array=np.array(indus_counts_array)

y_indus_counts_array=indus_counts_array/2.0

axis_map = {

“Current Location”:location,

“Current Industry”:industry,

“Current Company”:company

}

y_map ={

“Current Location”:local_counts1,

“Current Industry”:industry_counts1

}

height_map={

“Current Location”:y_local_height,

“Current Industry”:y_indus_height,

“Current Company”:y_company_height

}

new_axis_map={

“Current Location”:‘location’,

“Current Industry”:‘industry’,

“Current Company”:‘company’

}

source = ColumnDataSource(data=dict(x=,y=,height=))

cities=TextInput(title=‘location name’)

companies=TextInput(title=‘company name’)

industries=TextInput(title=‘industry name’)

x_axis=Select(title=‘X axis’,options=sorted(axis_map.keys()),value=‘Current Industry’)

plot = figure(plot_height=600, plot_width=800, title="", toolbar_location=None, tools=[hover],x_range=industry[:10],y_range=[0,2000])

plot.rect(x=‘x’,y=‘y’,width=.8,height=‘height’,source=source)

plot.xaxis.major_label_orientation = np.pi/3

controls=[x_axis,cities,companies,industries]

inputs=HBox(VBoxForm(*controls))

def select_types():

city_val=cities.value.strip()

company_val=companies.value.strip()

industry_val=industries.value.strip()

selected=data_all.copy()

if(city_val!=""):

selected=selected[selected[‘location’].str.contains(city_val)==True]

if(company_val!=""):

selected=selected[selected[‘company’].str.contains(company_val)==True]

if(industry_val!=""):

selected=selected[selected[‘industry’].str.contains(industry_val)==True]

return selected

def update(attrname,old,new):

df=select_types()

#plot.xaxis.axis_label=x_axis.value

plot.yaxis.axis_label=‘numbers’

if df.equals(data_all)==True:

source.data=dict(

x=axis_map[x_axis.value][:10],

y=height_map[x_axis.value][:10],

height=height_map[x_axis.value][:10]*2.0

)

plot.tools=[hover]

plot.xaxis.major_label_orientation = np.pi/3

plot.x_range.factors=axis_map[x_axis.value][:10]

height_value=height_map[x_axis.value][:10]*2

new_height=height_value.values

plot.y_range.end=new_height[0]+200

else:

df=df[new_axis_map[x_axis.value]].value_counts()

df.to_csv(‘example.csv’,sep=’,’)

df_counts=pd.read_csv(‘example.csv’,names=[new_axis_map[x_axis.value],‘numbers’],sep=’,’)

d=df_counts[new_axis_map[x_axis.value]].values

np.savetxt(‘here5.csv’,d,fmt=’%s’)

here=np.loadtxt(‘here5.csv’,str,delimiter=’\n’)

here=list(here)

here_height=df_counts[‘numbers’]

y_here_height=here_height/2.0

source.data=dict(

x=here[:10],

y=y_here_height[:10],

height=here_height[:10]

)

plot.tools=[hover]

plot.xaxis.major_label_orientation=np.pi/3

plot.x_range.factors=here[:10]

new_height=here_height[:10].values

plot.y_range.end=new_height[0]+200

#plot.rect(x=axis_map[x_axis.value],y=height_map[x_axis.value],height=height_map[x_axis.value]*2.0)

#plot.x_range.on_change(’_bounds_as_factors’,update)

x_axis.on_change(‘value’,update)

cities.on_change(‘value’,update)

companies.on_change(‘value’,update)

industries.on_change(‘value’,update)

#filters=VBox(x_axis)

#tot=HBox(filters,plot)

#show(tot)

curdoc().add_root(HBox(inputs,plot))

this is my complete code, and I can’t upload my results file.

在 2016年6月6日星期一 UTC+8上午2:25:49,Bryan Van de ven写道:

···

Please provide a complete code sample. That is, one that someone could immediately run without modification, to see the problem. I can’t speculate about what the issue might be without running the code, and I can’t run it if it is not a complete script. Also FYI I am technically on vacation so any response from me will probably be at least a few days away.

Bryan

On Jun 5, 2016, at 02:40, Qiwei Peng [email protected] wrote:

firstly: this is my update code:

def update(attrname,old,new):

plot.xaxis.axis_label=x_axis.value

plot.yaxis.axis_label=‘numbers’

source.data=dict(

x=axis_map[x_axis.value],

y=height_map[x_axis.value],

height=height_map[x_axis.value]*2.0

)

plot.x_range.factors=axis_map[x_axis.value]

plot.rect(x=axis_map[x_axis.value],y=height_map[x_axis.value],height=height_map[x_axis.value]*2.0)

after updating only the first bar shows its hover while the other bars don’t :

secondly: you may see the x_axis name above, they are too long to show correctly, how can I change them to an angle so to show correctly like bar chart’s x_axis

many thanks

You received this message because you are subscribed to the Google Groups “Bokeh Discussion - Public” group.

To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].

To post to this group, send email to [email protected].

To view this discussion on the web visit https://groups.google.com/a/continuum.io/d/msgid/bokeh/2d1ff885-5f4d-45e1-90f0-4ed32ebe615f%40continuum.io.

For more options, visit https://groups.google.com/a/continuum.io/d/optout.