Python Plotly：將水平線添加到具有多個子圖的散點 plot

Question

我有一個散點圖 plot 在 Plotly 儀表板上運行。 這是代碼：

import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly
import plotly.graph_objs as go
from plotly.subplots import make_subplots
import numpy as np

fig = make_subplots(rows=2, cols=3, vertical_spacing=0,
                    horizontal_spacing=0.05, shared_xaxes=True, shared_yaxes=False)
fig.add_trace(go.Scatter(x=list(range(40)), y=np.random.randint(20, 40, 40), line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x1', yaxis='y1'), row=1, col=1)
fig.add_trace(go.Scatter(x=list(range(40)), y=np.random.randint(100, 140, 40), line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x2', yaxis='y2'), row=1, col=2)
fig.add_trace(go.Scatter(x=list(range(40)), y=np.random.randint(20, 40, 40), line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x3', yaxis='y3'), row=1, col=3)
fig.add_trace(go.Scatter(x=list(range(40)), y=np.random.randint(20, 40, 40), line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x4', yaxis='y4'), row=2, col=1)
fig.add_trace(go.Scatter(x=list(range(40)), y=np.random.randint(100, 140, 40), line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x5', yaxis='y5'), row=2, col=2)
fig.add_trace(go.Scatter(x=list(range(40)), y=np.random.randint(20, 40, 40), line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x6', yaxis='y6'), row=2, col=3)
fig.add_shape(go.layout.Shape(type='line', yref='y3', xref='x3', x0=0, x1=30, y0=30, y1=30,
                          line=dict(color='red', width=3)))

fig.update_layout({'plot_bgcolor': "#21201f", 'paper_bgcolor': "#21201f", 'legend_orientation': "h"},
                  legend=dict(y=1, x=0),
                  font=dict(color='#dedddc'), dragmode='pan', hovermode='x unified',
                  margin=dict(b=20, t=0, l=0, r=40))

fig.update_xaxes(showgrid=False, zeroline=False, rangeslider_visible=False, showticklabels=False,
                 showspikes=True, spikemode='across', spikesnap='data', showline=False, spikedash='dash',
                 spikecolor='#ebeae8', spikethickness=0.5)
fig.update_yaxes(showgrid=False, zeroline=False, showticklabels=True, showline=False)

fig.update_traces(xaxis='x1', col=1)
fig.update_traces(xaxis='x2', col=2)
fig.update_traces(xaxis='x3', col=3)

app = dash.Dash(__name__)

app.layout = html.Div(children=[
    dcc.Graph(id='chart1', figure=fig,

              config={'displayModeBar': False})
])

if __name__ == '__main__':
    app.run_server(debug=True, dev_tools_ui=False, dev_tools_props_check=False)

它為這個特定的子圖畫了一條線。

但是，如果我將xref和yref更改為第二行的子圖（例如xref='x4'和yref='y4' ）它就不再起作用了。 我嘗試了這個問題的答案。

我遇到的另一個可能與上述問題有關的問題是第二行的 ylabels 與第一行的不同。 我希望他們像第一排一樣。 我在下圖中強調了我的意思。

Answer 1

下面的代碼采用與您類似的數據樣本，計算每列的平均值，並將其作為水平線添加到每個子圖中以生成此 plot：

我已經從您的原始片段中刪除了一些似乎把事情搞砸的元素。 我也忽略了破折號元素，因為它們不是生成最小可重現示例所必需的。

代碼：

#import dash
#import dash_core_components as dcc
#import dash_html_components as html
import plotly
import plotly.graph_objs as go
from plotly.subplots import make_subplots
import numpy as np
import pandas as pd

np.random.seed(123)
df=pd.DataFrame({ 'x':list(range(40)),
                    'y1':np.random.randint(20, 40, 40),
                    'y2':np.random.randint(100, 140, 40),
                    'y3':np.random.randint(20, 40, 40),
                    'y4':np.random.randint(20, 40, 40),
                    'y5':np.random.randint(100, 140, 40),
                    'y6':np.random.randint(20, 40, 40)})
df.set_index('x')

fig = make_subplots(rows=2, cols=3, vertical_spacing=0.1,
                    horizontal_spacing=0.1, shared_xaxes=True, shared_yaxes=False)

fig.add_trace(go.Scatter(x=list(range(40)), y=df['y1'], line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x1', yaxis='y1'), row=1, col=1)

fig.add_trace(go.Scatter(x=list(range(40)), y=df['y2'], line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x2', yaxis='y2'), row=1, col=2)

fig.add_trace(go.Scatter(x=list(range(40)), y=df['y3'], line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x3', yaxis='y3'), row=1, col=3)

fig.add_trace(go.Scatter(x=list(range(40)), y=df['y4'], line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x4', yaxis='y4'), row=2, col=1)

fig.add_trace(go.Scatter(x=list(range(40)), y=df['y5'], line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x5', yaxis='y5'), row=2, col=2)

fig.add_trace(go.Scatter(x=list(range(40)), y=df['y6'], line_color='#fae823', showlegend=False,
                         hovertemplate=[], xaxis='x6', yaxis='y6'), row=2, col=3)

fig.update_layout({'plot_bgcolor': "#21201f", 'paper_bgcolor': "#21201f", 'legend_orientation': "h"},
                  legend=dict(y=1, x=0),
                  font=dict(color='#dedddc'), dragmode='pan', hovermode='x unified',
                  margin=dict(b=20, t=0, l=0, r=40))

fig.update_xaxes(showgrid=False, zeroline=False, rangeslider_visible=False, showticklabels=False,
                 showspikes=True, spikemode='across', spikesnap='data', showline=False, spikedash='dash',
                 spikecolor='#ebeae8', spikethickness=0.5)

fig.update_yaxes(showgrid=False, zeroline=False, showticklabels=True, showline=False)

# add shapes
col_count = 1
for i in range(1,3):
    for j in range(1,4):
        fig.add_shape(go.layout.Shape(type="line",
                                        yref="paper",
                                        xref="x",
                                        x0=1,
                                        y0=df.iloc[:, col_count].mean(),
                                        x1=40,
                                        y1=df.iloc[:,col_count].mean(),
                                        #line=dict(color="RoyalBlue", width=3),),
                                        line=dict(color='red', width=3),),
                      row=i,
                      col=j)
        col_count = col_count+1

#fig.update_traces(xaxis='x1', col=1)
#fig.update_traces(xaxis='x2', col=2)
#fig.update_traces(xaxis='x3', col=3)
fig.show()