python - 使用 Plotly 自定义标签

Question

我正在尝试自定义悬停时显示的数据标签: 这是给我上面输出的代码:

import pandas as pd
import plotly.plotly as py
import plotly.graph_objs as go

# Create random data
labels = ['A', 'B', 'C']
N = 20
df = pd.DataFrame(index = range(N))
standardized_cols = []

for col in labels:
    df[col] = np.random.randn(N)
    standardized_colname  =  col + "_standardized"
    standardized_cols.append(standardized_colname)
    df[standardized_colname] = (df[col]-df[col].mean())/df[col].std()

# Cluster
c = KMeans(n_clusters=3, random_state=1).fit(df[standardized_cols]).labels_

# Plot
trace = go.Scatter3d(
    x=df.A_standardized,
    y=df.B_standardized,
    z=df.C_standardized,

    mode='markers',
    marker=dict(
        size=5,
        color=c,              
        colorscale='Viridis',   
    ),
    name= 'test',
    text= c
)

data = [trace]

fig = go.Figure(data=data, layout=layout)
iplot(fig)

我的数据: ]

该图表显示了标准化列的聚类。 但是，当将鼠标悬停在数据上时，我希望看到标签中的非标准化数据，即类似于

A: 0,999
B: 0,565
C: 0,765
Cluster: 2

我进行了实验，但不知道如何实现这一目标。这可能吗？

Answer 1

您可以进行一些列表理解并添加您想要的任何列文本请参阅下面的示例(注意，我正在离线绘制):

# data
np.random.seed(1)
labels = ['A', 'B', 'C']
N = 20
df = pd.DataFrame(index = range(N))
standardized_cols = []

for col in labels:
    df[col] = np.random.randn(N)
    standardized_colname  =  col + "_standardized"
    standardized_cols.append(standardized_colname)
    df[standardized_colname] = (df[col]-df[col].mean())/df[col].std()

c = KMeans(n_clusters=3, random_state=1).fit(df[standardized_cols]).labels_

plotly :

import plotly as py
import plotly.graph_objs as go


trace = go.Scatter3d(
    x=df.A_standardized,
    y=df.B_standardized,
    z=df.C_standardized,

    mode='markers',
    marker=dict(
        size=5,
        color=c,              
        colorscale='Viridis',   
    ),
    name= 'test',

    # list comprehension to add text on hover
    text= [f"A: {a}<br>B: {b}<br>C: {c}" for a,b,c in list(zip(df['A'], df['B'], df['C']))],
    # if you do not want to display x,y,z
    # hoverinfo='text'


)


layout = dict(title = 'TEST',)

data = [trace]
fig = dict(data=data, layout=layout)

py.offline.plot(fig, filename = 'stackTest.html')

您可以修改列表理解以显示您想要的任何内容

如果您不想显示x,y,z，请添加hoverinfo='text'