从Plotly的DataFrame列中添加多个文本标签

Question

目的是使用plotly文本参数包含多个列的位置绘制一些数据。

这是我的DataFrame：

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

np.random.seed(1)
df = pd.DataFrame({'Mean Age': np.random.randint(40,60,10),
                   'Percent': np.random.randint(20,80,10),
                   'Number Column': np.random.randint(100,500,10)},
                  index=list('ABCDEFGHIJ'))

df.index.name = 'Text Column'
df = df.sort_values('Mean Age')

这是一个示例，该示例显示了如何绘制带有一列文本的数据以在悬停时显示：

# trace for Percent
trace0 = go.Scatter(
    x = df.index,
    y = df['Percent'],
    name = 'Percent',
    text = df['Mean Age'], # text to show on hover from df column
    mode = 'lines+markers',
    line = dict(
        color = ('rgb(0,0,255)'), # blue
        width = 4)
)

layout = dict(title = 'Test Plot',
             xaxis = dict(title = 'Text Column'),
             yaxis = dict(title = 'Percent'),
              )

data = [trace0]
fig = dict(data=data, layout=layout)

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

我想将另一列的数据添加到text参数中。我可以通过一些列表理解来完成此操作，但是有没有更简单/有效的方法来做到这一点？

我正在寻找与下面类似的输出，但是比使用列表理解更有效的方式：

# column values to list
num = list(df['Number Column'])
age = list(df['Mean Age'])


# trace for Percent
trace0 = go.Scatter(
    x = df.index,
    y = df['Percent'],
    name = 'Percent',
    # list comprehension to get the data to show
    text = [f'Number Column: {x}; Mean Age: {y}' for x,y in list(zip(num, age))],
    mode = 'lines+markers',
    line = dict(
        color = ('rgb(0,0,255)'), # blue
        width = 4)
)

layout = dict(title = 'Test Plot',
             xaxis = dict(title = 'Text Column'),
             yaxis = dict(title = 'Percent'),
              )

data = [trace0]
fig = dict(data=data, layout=layout)

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

Answer 1

您还可以执行以下操作：

trace0 = go.Scatter(
    x = df.index,
    y = df['Percent'],
    name = 'Percent',
    # string concatenation in pandas
    # also the <br> puts the data on a new line in the hover text
    text = "Number Column: " + df["Number Column"].astype(str) + "<br>Mean Age: " + df["Mean Age"].astype(str),
    mode = 'lines+markers',
    line = dict(
        color = ('rgb(0,0,255)'),  # blue
        width = 4)
)