javascript-Bokeh Python；在ColumnDataSource上使用回调以使用“选择”小组件更改堆积的条形图
作者：互联网
我正在尝试使用具有bokeh(python)的Java脚本回调来在给定选择窗口小部件值时更改堆积的条形图.我正在使用矩形字形来构建堆积的条形图.每个栏都是一个年龄组,我的小部件应选择一个年龄组来显示.我需要做的就是告诉图表停止渲染其他矩形字形,并将一个年龄组的y值更改为等于其高度(从而使其成为简单的条形图).
我将所有数据存储在数组中,但随后将其转换为列表,以将其传递给回调.我的Java脚本警报告诉我,我的for语句有效,并且正在读取y值.回调的逻辑可能是时髦的/不正确的,但是我更加担心一个事实,即字形根本不会响应回调而改变.也许这是我在回调中推送数据的方式？谢谢！！
from bokeh.models import Callback, ColumnDataSource, Rect, Select
from bokeh.plotting import figure, output_file, show, VBox, gridplot, HBox
import pandas as pd
#Color Dictionary
redcolor5 = {u'All ages': "#720017", u'70+ years': "#bd0026", u'50-69 years': "#f03b20", u'15-49 years': "#fd8d3c", u'Under 5 years': "#f4cc63", u'gridline': '#b2ada6', u'background': '#e3e0db', u'axis' : '#aba9a7'}
#Just a sample of my data
country_both = ['China', 'India', 'United States', 'Russia', 'Japan', 'Indonesia', 'Germany', 'United Kingdom', 'Italy', 'Brazil']
ages_gen = ['Under 5 years', '15-49 years', '50-69 years', '70+ years', 'All ages', 'Age-standardized']
height70yr = [919470, 421922, 321125, 193960, 148946, 107822, 97529, 90198, 81107, 76782]
height50to69 = [640496, 626995, 182338, 195472, 40422, 109242, 44161, 33333, 24964, 64429]
height15to49 = [126094, 139420, 26159, 43239, 5480, 39040, 6829, 4163, 3571, 16152]
heightUnder5 = [10210, 43338, 82, 714, 41, 5255, 0, 26, 0, 1201]
frame = pd.DataFrame({"arBoth_70yr_Cnty": height70yr, "arBoth_5069yr_Cnty": height50to69, "arBoth_1549yr_Cnty": height15to49, "arBoth_5yr_Cnty": heightUnder5})
arBoth_70yr_Cnty = frame['arBoth_70yr_Cnty']
arBoth_5069yr_Cnty = frame['arBoth_5069yr_Cnty']
arBoth_1549yr_Cnty = frame['arBoth_1549yr_Cnty']
arBoth_5yr_Cnty = frame['arBoth_5yr_Cnty']
#Y Values for Stacked bar chart
yUnder5 = (arBoth_5yr_Cnty/2).tolist()
y15to49 = (arBoth_5yr_Cnty+arBoth_1549yr_Cnty/2).tolist()
y50to69 = (arBoth_5yr_Cnty+arBoth_1549yr_Cnty+arBoth_5069yr_Cnty/2).tolist()
y70yr = (arBoth_5yr_Cnty+arBoth_1549yr_Cnty+arBoth_5069yr_Cnty+arBoth_70yr_Cnty/2).tolist()
output_file('UW_TobaccoDeath.html')
#Figure for Stacked bar chart
p1 = figure(title="Top Countries with Death Due to Tobacco by Age",
x_range=country_both, y_range=[0, max(arBoth_5yr_Cnty+arBoth_1549yr_Cnty+arBoth_5069yr_Cnty+arBoth_70yr_Cnty)],
background_fill=redcolor5['background'],
plot_width=700, plot_height = 400,
outline_line_color= None)
#source for callback
source1 = ColumnDataSource(data=dict(x=country_both, yUnder5 = yUnder5, heightUnder5 = heightUnder5, y15to49 = y15to49, height15to49 = height15to49, y50to69 = y50to69, height50to69 = height50to69, y70yr=y70yr, height70yr = height70yr))
#Use rect glyphs for stached bars
p1.rect(x ='x', y ='yUnder5', width =.8, height = 'heightUnder5', source = source1, color=redcolor5['Under 5 years'], alpha=0.8, name = "Under 5")
p1.rect(x = 'x', y ='y15to49', width = .8, height ='height15to49', source = source1, color=redcolor5['15-49 years'], alpha=0.8, name = "15 to 49")
p1.rect(x = 'x', y ='y50to69', width = .8, height ='height50to69', source = source1, color=redcolor5['50-69 years'], alpha = .8, name = "50 to 69")
p1.rect(x = 'x', y ='y70yr', width = .8, height ='height70yr', source = source1, color=redcolor5['70+ years'], alpha = .8, name = "70+ yrs")
#Java script Callbacks for age
#I want this to recognize the 70+ year old drop down selection
#and change the plot so that the height of the glyph is the same as the y value and the 70 year old glyph is the only one that displays
Callback_Age = Callback(args=dict(source1 = source1), code="""
var f = cb_obj.get('value');
var data = source1.get('data');
var x = data['x'];
if (f == '70+ years') {
var y = 0;
var height = data['height70yr'];
alert(height);
}
data['x'].push(x);
data['y'].push(y);
data['height'].push(height);
source1.trigger('change');
""")
#Use the Select widget
dropdown_age = Select(title="Ages:", value=ages_gen[4], options= ages_gen, callback = Callback_Age)
#Display data
filters = VBox(dropdown_age)
tot = HBox(filters, gridplot([[p1]]))
show(tot)
解决方法:
感谢您研究与烟草有关的伤亡！
我要做的事情是使用4个来源(每个年龄段1个),然后根据所选的年龄段手动更改它们.如果选择了15-49岁年龄段,则相关来源y的中心向下(到高度/ 0),而所有其他高度的高度都设置为0.我已经完成了“所有年龄段”,但未进行“年龄标准化”.我也没有尝试调整数字以更好地观察5岁以下人群.
哦,我也换成numpy数组.这只是一个方便的事情,如果您愿意,可以继续使用Python列表和Panda框架.
问我是否还有其他问题,
蒂埃里
from bokeh.models import Callback, ColumnDataSource, Rect, Select,CustomJS
from bokeh.plotting import figure, output_file, show, gridplot
from bokeh.models.widgets.layouts import VBox,HBox
import numpy as np
#Color Dictionary
redcolor5 = {u'All ages': "#720017", u'70+ years': "#bd0026", u'50-69 years': "#f03b20", u'15-49 years': "#fd8d3c", u'Under 5 years': "#f4cc63", u'gridline': '#b2ada6', u'background': '#e3e0db', u'axis' : '#aba9a7'}
#Just a sample of my data
country_both = ['China', 'India', 'United States', 'Russia', 'Japan', 'Indonesia', 'Germany', 'United Kingdom', 'Italy', 'Brazil']
ages_gen = ['Under 5 years', '15-49 years', '50-69 years', '70+ years', 'All ages', 'Age-standardized']
height70yr = np.array([919470, 421922, 321125, 193960, 148946, 107822, 97529, 90198, 81107, 76782])
height50to69 = np.array([640496, 626995, 182338, 195472, 40422, 109242, 44161, 33333, 24964, 64429])
height15to49 = np.array([126094, 139420, 26159, 43239, 5480, 39040, 6829, 4163, 3571, 16152])
heightUnder5 = np.array([10210, 43338, 82, 714, 41, 5255, 0, 26, 0, 1201])
zeros = np.zeros(len(country_both))
#Y Values for Stacked bar chart
yUnder5 = heightUnder5 / 2.0
y15to49 = yUnder5 + height15to49/2.0
y50to69 = y15to49 + height50to69/2.0
y70yr = y50to69 + height70yr/2.0
output_file('UW_TobaccoDeath.html')
#Figure for Stacked bar chart
p1 = figure(title="Top Countries with Death Due to Tobacco by Age",
x_range=country_both, y_range=[0, np.amax([y70yr+height70yr])],
background_fill=redcolor5['background'],
plot_width=700, plot_height = 600,
outline_line_color= None)
#source for callback
source1 = ColumnDataSource(data=dict(x=country_both, y = yUnder5, y_full = yUnder5, height = heightUnder5, height_full = heightUnder5 ,height_zeros = zeros, y_zeros = heightUnder5 / 2.0))
source2 = ColumnDataSource(data=dict(x=country_both, y = y15to49, y_full = y15to49, height = height15to49, height_full = height15to49,height_zeros = zeros, y_zeros = height15to49 / 2.0))
source3 = ColumnDataSource(data=dict(x=country_both, y = y50to69, y_full = y50to69, height = height50to69, height_full = height50to69,height_zeros = zeros , y_zeros = height50to69 / 2.0))
source4 = ColumnDataSource(data=dict(x=country_both, y = y70yr, y_full = y70yr, height = height70yr, height_full = height70yr,height_zeros = zeros, y_zeros = height70yr / 2.0))
#Use rect glyphs for stached bars
p1.rect(x ='x', y ='y', width =.8, height = 'height', source = source1, color=redcolor5['Under 5 years'], alpha=0.8, name = "Under 5")
p1.rect(x = 'x', y ='y', width = .8, height ='height', source = source2, color=redcolor5['15-49 years'], alpha=0.8, name = "15 to 49")
p1.rect(x = 'x', y ='y', width = .8, height ='height', source = source3, color=redcolor5['50-69 years'], alpha = .8, name = "50 to 69")
p1.rect(x = 'x', y ='y', width = .8, height ='height', source = source4, color=redcolor5['70+ years'], alpha = .8, name = "70+ yrs")
#Java script Callbacks for age
#I want this to recognize the 70+ year old drop down selection
#and change the plot so that the height of the glyph is the same as the y value and the 70 year old glyph is the only one that displays
Callback_Age = CustomJS(args={'source1': source1,'source2': source2,'source3': source3,'source4': source4}, code="""
var f = cb_obj.get('value');
var data1 = source1.get('data');
var data2 = source2.get('data');
var data3 = source3.get('data');
var data4 = source4.get('data');
if (f == 'Under 5 years') {
data3['height'] = data3['height_zeros'];
data2['height'] = data2['height_zeros'];
data4['height'] = data4['height_zeros'];
data1['y'] = data1['y_zeros'];
data1['height'] = data1['height_full'];
source1.trigger('change');
source2.trigger('change');
source3.trigger('change');
source4.trigger('change');
}
if (f == '15-49 years') {
data1['height'] = data1['height_zeros'];
data3['height'] = data3['height_zeros'];
data4['height'] = data4['height_zeros'];
data2['y'] = data2['y_zeros'];
data2['height'] = data2['height_full'];
source1.trigger('change');
source2.trigger('change');
source3.trigger('change');
source4.trigger('change');
}
if (f == '50-69 years') {
data1['height'] = data1['height_zeros'];
data2['height'] = data2['height_zeros'];
data4['height'] = data4['height_zeros'];
data3['y'] = data3['y_zeros'];
data3['height'] = data3['height_full'];
console.log('data3',data3)
source1.trigger('change');
source2.trigger('change');
source3.trigger('change');
source4.trigger('change');
}
if (f == '70+ years') {
data1['height'] = data1['height_zeros'];
data2['height'] = data2['height_zeros'];
data3['height'] = data3['height_zeros'];
data4['y'] = data4['y_zeros'];
data4['height'] = data4['height_full'];
source1.trigger('change');
source2.trigger('change');
source3.trigger('change');
source4.trigger('change');
}
if (f == 'All ages') {
data1['height'] = data1['height_full'];
data1['y'] = data1['y_full'];
data2['height'] = data2['height_full'];
data2['y'] = data2['y_full'];
data3['height'] = data3['height_full'];
data3['y'] = data3['y_full'];
data4['height'] = data4['height_full'];
data4['y'] = data4['y_full'];
source1.trigger('change');
source2.trigger('change');
source3.trigger('change');
source4.trigger('change');
}
""")
#Use the Select widget
dropdown_age = Select(title="Ages:", value=ages_gen[4], options= ages_gen, callback = Callback_Age)
#Display data
filters = VBox(dropdown_age)
tot = HBox(filters, gridplot([[p1]]))
show(tot)
标签：callback,data-visualization,bokeh,javascript,python 来源： https://codeday.me/bug/20191119/2036659.html