我是 Bokeh 新手，正在尝试使用 CustomJS 实现 Slider 回调。我的销售数据按年、月、日分组。根据 slider 值(1-12)，我的每月数据必须在绘图上更改。下面是我的代码: slider 值(0-12)- 月份数字 X 轴:天(1-30) y 轴:销售额
df3=df
df3['Date2'] = pd.to_datetime(df['Inv Date'])
df3.set_index('Date2', inplace=True)
df3['month'] = df3.index.month
df3['year'] = df3.index.year
df3['day'] = df3.index.day
df3['Dateday'] = pd.to_datetime(df3[['year','month', 'day']])
source1=df3.groupby(['year','month','day'], as_index = False).sum()
current_month=ColumnDataSource(source1[source1['year']== dt.now().year])
hover3 = HoverTool(
tooltips = [
('day', '@day'),
('Sales','@{Sales}{0,0}'),
],
formatters = {
'day': 'datetime',
'Sales': 'numeral'}
)
p = figure(
title='YEARLY SALES',
plot_width=600,
plot_height=400,
min_border=3,
tools = [hover3,'box_zoom','wheel_zoom', 'pan','reset'],
toolbar_location="above")
p.vbar(x='day', top='Sales', width=0.2, color='#e8bc76',
source=current_month)
p.xaxis.axis_label = 'Day'
p.xaxis.axis_label_text_font_style = 'normal'
p.xaxis.axis_label_text_font_size = '12pt'
p.yaxis[0].formatter = NumeralTickFormatter(format="0,0")
callback = CustomJS(args=dict(source=current_month), code="""
var f = slider.get('value');
var data = source.data;
data1=current_month[current_month['month']== f]
day=data1[data1['day']]
Sales=data1[data1['Sales']]
source.trigger('change');
""")
slider = Slider(start=1, end=12, value=1, step=1, title="power",
callback=callback)
layout = column(slider, p)
show(layout)
谁能帮帮我。我被困在这里根据自定义回调过滤我的数据帧。
最佳答案
如果您想使用可以调用 native Python 回调函数的 bokehserve，这将相当快。这也可以使用 javascript 回调 CustomJS 实现。
由于我没有您的数据，因此我使用以下代码生成了虚拟数据 -
import pandas as pd
import random
from datetime import timedelta
df = pd.DataFrame({'base' : ["2017-01-01" for t in range(10000)],
'Date' : [random.randint(0, 1035) for t in range(10000)],
'Sales' : [random.random() for t in range(10000)]})
df['base'] = pd.to_datetime(df['base'])
df["Date2"] = df.apply(lambda x: x["base"] + timedelta(days=x['Date']), axis=1)
df.drop(['base', 'Date'], axis=1, inplace=True)
这将提供 2017 年至 2019 年之间的 10000 行随机销售。在下面的示例中，我仅过滤了 2017 年。
在下一步中，我将生成两个 ColumnDataSource - 一个用于 2017 年所有数据，另一个仅用于 2017 年第 1 个月的数据 - 以创建初始图表。第二个将用于生成 vbar
from bokeh.models.widgets import Slider
from bokeh.layouts import widgetbox, column
from bokeh.models import Slider, ColumnDataSource, CustomJS
from bokeh.plotting import figure, curdoc
from bokeh.core.properties import value
from bokeh.models.ranges import FactorRange
from bokeh.plotting import figure, output_file, show, ColumnDataSource
from bokeh.models import ColumnDataSource, CDSView, IndexFilter, BooleanFilter, HoverTool
df.set_index('Date2', inplace=True)
df['month'] = df.index.month
df['year'] = df.index.year
df['day'] = df.index.day
source1=df.groupby(['year','month','day'], as_index = False).sum()
source = source1[source1['year']== 2017]
sourcex = source[source['month'] ==1]
Overall=ColumnDataSource(source)
Curr=ColumnDataSource(sourcex)
boolinit = source['month']==1
view = CDSView(source=Overall, filters=[BooleanFilter(boolinit)])
hover3 = HoverTool(tooltips = [('day', '@day'),('Sales','@{Sales}{0,0}')],
formatters = {'day': 'datetime','Sales': 'numeral'})
p = figure(title='YEARLY SALES', plot_width=600, plot_height=400, min_border=3,
tools = [hover3,'box_zoom','wheel_zoom', 'pan','reset'],
toolbar_location="above")
r = p.vbar(x='day', top='Sales', width=0.2, color='#e8bc76', source=Curr)
p.xaxis.axis_label = 'Day'
p.xaxis.axis_label_text_font_style = 'normal'
p.xaxis.axis_label_text_font_size = '12pt'
现在，我们将编写 JavaScript 回调函数，它将通过在整个 ColumnDataSource 上应用过滤器来更改 vbar 中使用的 ColumnDataSource。将其添加到 slider 回调中，我们就有了一个基于 javascript 的数据过滤器 -
callback = CustomJS(args=dict(source=Overall, sc=Curr), code="""
var f = slider.value;
sc.data['x'] = [];
sc.data['top'] = [];
for (var i = 0; i <= source.get_length(); i++){
if (source.data['month'][i] == f){
sc.data['day'].push(source.data['day'][i])
sc.data['Sales'].push(source.data['Sales'][i])
}
}
sc.change.emit();
""")
slider = Slider(start=1, end=12, value=1, step=1, title="Month", callback=callback)
callback.args["slider"] = slider
layout = column(slider, p)
output_file("Filterdata.html")
#fig.view.filters[0].booleans = indices
show(layout)
这将生成以下类型的 HTML -
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Bokeh Plot</title>
<link rel="stylesheet" href="https://cdn.bokeh.org/bokeh/release/bokeh-0.12.16.min.css" type="text/css" />
<link rel="stylesheet" href="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-0.12.16.min.css" type="text/css" />
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-0.12.16.min.js"></script>
<script type="text/javascript" src="https://cdn.bokeh.org/bokeh/release/bokeh-widgets-0.12.16.min.js"></script>
<script type="text/javascript">
Bokeh.set_log_level("info");
</script>
</head>
<body>
<div class="bk-root">
<div class="bk-plotdiv" id="1b4d2791-052d-4f87-b697-2703d126d006"></div>
</div>
<script type="application/json" id="59b3ceeb-f6e4-457f-8243-236ad4e4ecc6">
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</body>
</html>关于python - Bokeh Slider自定义JS回调，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/50689700/