Python Plotly – 如何添加多个 Y 轴？

在本文中，让我们看看如何在Python中的 Plotly 图表中添加多个不同比例的 y 轴。

目前，Plotly Express 不支持单个图形上的多个 Y 轴。所以，我们将使用 Plotly go。 Plotly 提供了一个名为make_subplots()的函数来绘制具有多个 Y 轴的图表。

Syntax:

plotly.subplots.make_subplots(rows=1, cols=1, specs=None)

Parameter:

• rows: A number of rows in the subplot grid. (rows > 0). default 1
• cols: A number of columns in the subplot grid. (cols> 0). default 1
• specs: (list of lists of dict or None (default None)). Per subplot specifications of subplot type, row/column spanning, and spacing.

首先，从Plotly 包中导入必要的函数，并使用make_subplots()函数中的 specs 参数创建辅助轴，如图所示。绘制具有多个 y 轴的散点图。通过在x和y 轴上添加标题来使图表可读。

示例：添加 2 个 y 轴

Python3

# import graph_objects from plotly package
import plotly.graph_objects as go
 
# import make_subplots function from plotly.subplots
# to make grid of plots
from plotly.subplots import make_subplots
 
# use specs parameter in make_subplots function
# to create secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
 
# plot a scatter chart by specifying the x and y values
# Use add_trace function to specify secondary_y axes.
fig.add_trace(
    go.Scatter(x=[10, 20, 30], y=[400, 500, 600], name="yaxis values"),
    secondary_y=False)
 
# Use add_trace function and specify secondary_y axes = True.
fig.add_trace(
    go.Scatter(x=[20, 30, 40], y=[40, 50, 60], name="yaxis2 values"),
    secondary_y=True,)
 
# Adding title text to the figure
fig.update_layout(
    title_text="Multiple Y Axis in Plotly"
)
 
# Naming x-axis
fig.update_xaxes(title_text="X - axis")
 
# Naming y-axes
fig.update_yaxes(title_text="Main Y - axis ", secondary_y=False)
fig.update_yaxes(title_text="secondary Y - axis ", secondary_y=True)

输出：

绘制具有多个 y 轴的散点图

示例：添加 2 个 y 轴

Python3

# import graph_objects from plotly package
import plotly.graph_objects as go
 
# import make_subplots function from plotly.subplots
# to make grid of plots
from plotly.subplots import make_subplots
 
# use specs parameter in make_subplots function
# to create secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])
 
# plot a bar chart by specifying the x and y values
# Use add_trace function to specify secondary_y axes.
fig.add_trace(
    go.Bar(x=[10, 20, 30], y=[40, 50, 60], name="yaxis values"),
    secondary_y=False)
 
# Use add_trace function and specify secondary_y axes = True.
fig.add_trace(
    go.Bar(x=[20, 30, 40], y=[400, 500, 600], name="yaxis2 values"),
    secondary_y=True,)
 
# Adding title text to the figure
fig.update_layout(
    title_text="Multiple Y Axis in Plotly"
)
 
# Naming x-axis
fig.update_xaxes(title_text="X - axis")
 
# Naming y-axes
fig.update_yaxes(title_text="Main Y - axis ", secondary_y=False)
fig.update_yaxes(title_text="secondary Y - axis ", secondary_y=True)

输出：

绘制具有多个 y 轴的条形图

绘制具有多个 Y 轴的图表

现在，让我们看看如何绘制具有2 个以上 Y 轴或多个 Y 轴的散点图。过程同上，在图形布局部分进行了更改，使图表在视觉上更令人愉悦。

从Plotly 包中导入必要的函数。如图所示，使用make_subplots函数中的 specs 参数创建辅助轴。绘制具有多个 y 轴的散点图。

示例：添加多个 y 轴

Python3

# import the graph_objects function from
# plotly package
import plotly.graph_objects as go
 
# initialize a Figure object and store it in
# a variable fig
fig = go.Figure()
 
# add x and y values for the 1st scatter
# plot and name the yaxis as yaxis1 values
fig.add_trace(go.Scatter(
    x=[10, 12, 13],
    y=[41, 58, 60],
    name="yaxis1 values"
))
 
# add x and y values for the 2nd scatter
# plot and name the yaxis as yaxis2 values
fig.add_trace(go.Scatter(
    x=[12, 13, 14],
    y=[401, 501, 610],
    name="yaxis2 values",
    yaxis="y2"
))
 
# add x and y values for the 3rd scatter
# plot and name the yaxis as yaxis3 values
fig.add_trace(go.Scatter(
    x=[14, 15, 16],
    y=[42000, 53000, 65000],
    name="yaxis3 values",
    yaxis="y3"
))
 
# add x and y values for the 4th scatter plot
# and name the yaxis as yaxis4 values
fig.add_trace(go.Scatter(
    x=[15, 16, 17],
    y=[2000, 5000, 7000],
    name="yaxis4 values",
    yaxis="y4"
))
 
# Create axis objects
fig.update_layout(
    # split the x-axis to fraction of plots in
    # proportions
    xaxis=dict(
        domain=[0.3, 0.7]
    ),
   
    # pass the y-axis title, titlefont, color
    # and tickfont as a dictionary and store
    # it an variable yaxis
    yaxis=dict(
        title="yaxis 1",
        titlefont=dict(
            color="#0000ff"
        ),
        tickfont=dict(
            color="#0000ff"
        )
    ),
     
    # pass the y-axis 2 title, titlefont, color and
    # tickfont as a dictionary and store it an
    # variable yaxis 2
    yaxis2=dict(
        title="yaxis 2",
        titlefont=dict(
            color="#FF0000"
        ),
        tickfont=dict(
            color="#FF0000"
        ),
        anchor="free",  # specifying x - axis has to be the fixed
        overlaying="y",  # specifyinfg y - axis has to be separated
        side="left",  # specifying the side the axis should be present
        position=0.2  # specifying the position of the axis
    ),
   
    # pass the y-axis 3 title, titlefont, color and
    # tickfont as a dictionary and store it an
    # variable yaxis 3
    yaxis3=dict(
        title="yaxis 3",
        titlefont=dict(
            color="#006400"
        ),
        tickfont=dict(
            color="#006400"
        ),
        anchor="x",     # specifying x - axis has to be the fixed
        overlaying="y",  # specifyinfg y - axis has to be separated
        side="right"  # specifying the side the axis should be present
    ),
     
    # pass the y-axis 4 title, titlefont, color and
    # tickfont as a dictionary and store it an
    # variable yaxis 4
    yaxis4=dict(
        title="yaxis 4",
        titlefont=dict(
            color="#8f00ff"
        ),
        tickfont=dict(
            color="#8f00ff"
        ),
        anchor="free",  # specifying x - axis has to be the fixed
        overlaying="y",  # specifyinfg y - axis has to be separated
        side="right",  # specifying the side the axis should be present
        position=0.8  # specifying the position of the axis
    )
)
 
 
# Update layout of the plot namely title_text, width
# and place it in the center using title_x parameter
# as shown
fig.update_layout(
    title_text="4 y-axes scatter plot in plotly",
    width=1000,
    title_x=0.5
)

输出：

绘制具有多个 y 轴的散点图