Question

我正在尝试使用一个函数更新Bokeh散点图的数据源。但是，该图显示了所有数据，而不是仅绘制新数据。

我认为我正在将新的数据源传递给绘图，但是旧的绘图点仍然存在。

您如何仅用新数据更新散点图？

还可以在不与下拉菜单进行交互的情况下检索下拉菜单中的当前选择吗？（即没有使用on_change的回调）

import numpy as np
import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Tabs, Select
from bokeh.layouts import column, row, Spacer
from bokeh.io import curdoc
from bokeh.plotting import figure, curdoc, show

#Plotting points on initial chart.
df_AB = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('AB'), index=[str(i) for i in range(1,500+1)])
pointchart=figure(plot_width=800, plot_height=700, tools=['lasso_select','box_select'],title="Point scatter")
pointchart_source= ColumnDataSource(df_AB[["A","B"]])
pointchart_glyph= pointchart.circle("A","B",source=pointchart_source)

#Dropdown
selectoroptions=['','new selection', 'other selection']
Xselector = Select(title="Dropdown:", value="", options=selectoroptions)

#Callback to update data source
def Xdropdownchange(attrname, old, new):
        pointchart_glyph= pointchart.circle("X","Y",source=make_updated_source())

Xselector.on_change("value", Xdropdownchange)


#Making new/updated data source based on dropdowns.
df_XY = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('XY'), index=[str(i) for i in range(1,500+1)])

def make_updated_source():
    new_x=pd.Series(list(df_XY.iloc[0:100]["X"]),name="X")
    new_y=pd.Series(list(df_XY.iloc[0:100]["Y"]),name="Y")

    sourcedf=pd.DataFrame([new_x,new_y]).T
    pointchart_source= ColumnDataSource(sourcedf)
    return pointchart_source


#Show
layout=row(column(Xselector, Spacer(width=400, height=500)),pointchart)
curdoc().add_root(layout)
!powershell -command {'bokeh serve --show Dropdown_sourcechange.ipynb'}

Answer 1

我更改了代码中的某些内容，如果您在下拉列表中选择空值，或者在下拉列表中选择其他值之一时随机生成的数据集，则现在可以显示原始数据。 print(Xselector.value)

也可以在不使用回调的情况下检索下拉列表中的当前选择

import numpy as np
import pandas as pd
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Tabs, Select
from bokeh.layouts import column, row, Spacer
from bokeh.io import curdoc
from bokeh.plotting import figure, curdoc, show

#Plotting points on initial chart.
df_AB = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('XY'), index=[str(i) for i in range(1,500+1)])
pointchart=figure(plot_width=800, plot_height=700, tools=['lasso_select','box_select','wheel_zoom'],title="Point scatter")
source= ColumnDataSource(df_AB[["X","Y"]])
pointchart.circle("X","Y",source=source)

#Dropdown
selectoroptions=['','new selection', 'other selection']
Xselector = Select(title="Dropdown:", value="", options=selectoroptions)

def make_updated_source(attr, old, new):
    if new == '':
        source.data = ColumnDataSource(df_AB[["X","Y"]]).data
    else:
        df_XY = pd.DataFrame(np.random.randint(0,100,size=(500, 2)), columns=list('XY'), index=[str(i) for i in range(1,500+1)])
        new_x=pd.Series(list(df_XY.iloc[0:100]["X"]),name="X")
        new_y=pd.Series(list(df_XY.iloc[0:100]["Y"]),name="Y")
        sourcedf=pd.DataFrame([new_x,new_y]).T
        source.data = ColumnDataSource(sourcedf).data

Xselector.on_change("value", make_updated_source)

#Retrieve selection in dropdown withoud on_change
print(Xselector.value)

#Show
layout=row(column(Xselector, Spacer(width=400, height=500)),pointchart)
curdoc().add_root(layout)
!powershell -command {'bokeh serve --show Dropdown_sourcechange.ipynb'}

散景源更改

1 个答案: