python - Plotly:如何更改每个子图的背景颜色？

Question

我正在尝试创建不同的子图，我希望每个子图都有不同的背景颜色。我正在使用 plotly，它使事情变得更加困难。任何的想法？我认为 matplot 中的等价物是 face_color 或类似的东西。

fig = make_subplots(rows=1, cols=2)

fig.add_trace(
    go.Scatter(
        x=list(range(sample_points)),
        y=data_gx.iloc[scene],
        name='X-axis',
        line=dict(color='green', width=2)
    ),
    row=1, col=1
)

fig.add_trace(
    go.Scatter(
        x=list(range(sample_points)),
        y=data_ax.iloc[scene],
        name='X-axis',
        line=dict(color='green', width=2)
    ),
    row=1, col=2
)

Answer 1

不幸的是，似乎仍然不能设置different background colors对于不同的子图直接:

The background color is set in layout for the figure: plot_bgcolor='rgb(245,245,240)'. At the moment you cannot change the backround of a particular subplot.

但是 您可以通过 xref=x 引用两个 x 轴，将形状随意放置在两个子图中的任何位置。和 xref=x2在 fig.update_layout(shapes=dict()) .如果您确保调整其他一些参数以及零线和 layer='below'你会得到一个很好的结果:



完整代码:

# imports
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import pandas as pd
import numpy as np

# data
df = pd.DataFrame({'Index': {0: 1.0,
                              1: 2.0,
                              2: 3.0,
                              3: 4.0,
                              4: 5.0,
                              5: 6.0,
                              6: 7.0,
                              7: 8.0,
                              8: 9.0,
                              9: 10.0},
                             'A': {0: 15.0,
                              1: 6.0,
                              2: 5.0,
                              3: 4.0,
                              4: 3.0,
                              5: 2.0,
                              6: 1.0,
                              7: 0.5,
                              8: 0.3,
                              9: 0.1},
                             'B': {0: 1.0,
                              1: 4.0,
                              2: 2.0,
                              3: 5.0,
                              4: 4.0,
                              5: 6.0,
                              6: 7.0,
                              7: 2.0,
                              8: 8.0,
                              9: 1.0},
                             'C': {0: 12.0,
                              1: 6.0,
                              2: 5.0,
                              3: 4.0,
                              4: 3.0,
                              5: 2.0,
                              6: 1.0,
                              7: 0.5,
                              8: 0.2,
                              9: 0.1}})
# set up plotly figure
fig = make_subplots(1,2)

# add first bar trace at row = 1, col = 1
fig.add_trace(go.Bar(x=df['Index'], y=df['A'],
                     name='A',
                     marker_color = 'green',
                     opacity=0.4,
                     marker_line_color='rgba(0,0,0,0)',
                     marker_line_width=2),
              row = 1, col = 1)

# add first scatter trace at row = 1, col = 1
fig.add_trace(go.Scatter(x=df['Index'], y=df['B'], line=dict(color='red'), name='B'),
              row = 1, col = 1)

# add first bar trace at row = 1, col = 2
fig.add_trace(go.Bar(x=df['Index'], y=df['C'],
                     name='C',
                     marker_color = 'green',
                     opacity=0.4,
                     marker_line_color='rgba(0,0,0,0)',
                    marker_line_width=2),
              row = 1, col = 2)

fig.update_layout(plot_bgcolor='rgba(0,0,0,0)')

# Define gridlines and zerolines
# => an invisible zerolines looks better
# in this scenario
fig.update_layout(xaxis=dict(showgrid=False, zeroline=False),
                  yaxis=dict(showgrid=True, zeroline=False),
                  xaxis2=dict(showgrid=False, zeroline=False),
                  yaxis2=dict(showgrid=True, zeroline=False),

)

fig.update_layout(
    shapes=[
        # 1st highlight during Feb 4 - Feb 6
 dict(
            type="rect",
            xref="x",
            yref="paper",
            x0=df['Index'].iloc[0]-1,
            y0=-0.001,
            x1=df.index[-1]+2,
            y1=1,
            fillcolor="steelblue",
            opacity=0.5,
            layer="below",
            line_width=0,
        ),
        # 2nd highlight during Feb 20 - Feb 23
        dict(
            type="rect",
            xref="x2",
            yref="paper",
            x0=df['Index'].iloc[0]-1,
            y0=-0.001,
            x1=df.index[-1]+2,
            y1=1,
            fillcolor="firebrick",
            opacity=0.5,
            layer="below",
            line_width=0,
        )
    ]
)

fig.show()