根据他们的文档，我有以下内容:
album_names = ['Ctrl', 'Ctrl', 'Z', 'Ctrl', 'Ctrl', 'Z', 'Ctrl', 'Ctrl', 'Ctrl', 'Ctrl', 'Z', 'Z', 'Z', 'Z', 'Z', 'Z', 'Z', 'Ctrl', 'Ctrl', 'Ctrl', 'Ctrl', 'Ctrl', 'Ctrl', 'Z']
valence = [0.37, 0.598, 0.481, 0.166, 0.413, 0.0798, 0.549, 0.332, 0.348, 0.335, 0.355, 0.22, 0.433, 0.158, 0.357, 0.134, 0.367, 0.237, 0.248, 0.239, 0.535, 0.432, 0.505, 0.142]
energy = [0.579, 0.686, 0.551, 0.367, 0.61, 0.475, 0.488, 0.525, 0.534, 0.517, 0.56, 0.342, 0.688, 0.505, 0.551, 0.63, 0.71, 0.453, 0.518, 0.708, 0.463, 0.684, 0.296, 0.576]`
df = pd.DataFrame([album_names, energy, valence]).T
df.columns = ['album_name', 'energy', 'valence']
我想使用 Bokeh 绘制散点图，x 轴为化合价，y 轴为能量。此外，当您将鼠标悬停在每个点上时，我希望它说出它对 album_name 的值(value)。并且点的颜色是基于album_name。
我尝试了以下方法:
from bokeh.models import ColumnDataSource, Range1d, LabelSet, Label
from bokeh.io import output_notebook, show
from bokeh.plotting import figure
from bokeh.palettes import brewer
source = ColumnDataSource(data=dict(valence=valence,
energy=energy,
names=album_names))
p = figure()
p.scatter(x='valence', y='energy', size=8, source=source)
labels = LabelSet(x='valence', y='energy', text='names',
level='glyph', x_offset=5, y_offset=5,
source=source, render_mode='canvas')
p.add_layout(labels)
show(p)
但是当您将鼠标悬停在该点上时，这不会显示相册名称。它修复了点旁边的专辑名称。非常感谢仅在将鼠标悬停在该点上并根据 album_name 的值更改颜色时让 album_name 显示的任何帮助
请您参考如下方法:
检查它就可以了:
from bokeh.plotting import figure, ColumnDataSource, output_notebook, show
from bokeh.models import HoverTool, WheelZoomTool, PanTool, BoxZoomTool, ResetTool, TapTool, SaveTool
from bokeh.palettes import brewer
output_notebook()
#preprocessing the data with column album_name
category = 'album_name'
category_items = df[category].unique()
#selecting the colors for each unique category in album_name
palette = brewer['Set2'][len(category_items) + 1]
#mapping each category with a color of Set2
colormap = dict(zip(category_items, palette))
#making a color column based on album_name
df['color'] = df[category].map(colormap)
title = "Album_names"
#feeding data into ColumnDataSource
source = ColumnDataSource(df)
#Editing the hover that need to displayed while hovering
hover = HoverTool(tooltips=[('Album_name', '@album_name')])
#tools that are need to explote data
tools = [hover, WheelZoomTool(), PanTool(), BoxZoomTool(), ResetTool(), SaveTool()]
#finally making figure with scatter plot
p = figure(tools=tools,title=title,plot_width=700,plot_height=400,toolbar_location='right',toolbar_sticky=False, )
p.scatter(x='valence',y='energy',source=source,size=10,color='color',legend=category)
#displaying the graph
show(p)
