Python Plotly:向具有多个子图的散点图添加水平线 [英] Python Plotly: Adding a horizontal line to a scatter plot that has multiple subplots
问题描述
我有一个在 Plotly dash 上运行的散点图.这是代码:
I have a scatter plot that is running on Plotly dash. This is the code:
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)
它为这个特定的子图画线.
It draws the line for this particular subplot.
但是,如果我将 xref
和 yref
更改为第二行的子图(例如 xref='x4'
和 yref='y4'
) 它不再起作用.我尝试了这个
However, if I change the xref
and yref
to subplots of the second row (for example xref='x4'
and yref='y4'
) It doesn't work anymore. I tried the answer from this
我遇到的另一个可能与上述问题有关的问题是第二行的 ylabels 与第一行的 ylabels 不同.我希望它们像第一排一样.我在下图中强调了我的意思.
Another problem that I have that could be related to the above issue is that the ylabels for the second row are not the same as of first row. I want them to be like the first row. I highlighted what I mean in the figure below.
推荐答案
下面的代码采用与您相似的数据样本,计算每列的平均值,并将其作为水平线添加到每个子图以生成此图:
The code below takes a data sample similar to yours, calculates the mean for each column, and adds that as a horizontal line to each subplot to produce this plot:
我已从您的原始代码段中删除了一些似乎会使事情变得混乱的元素.我也忽略了破折号元素,因为它们不是生成最小可重现示例所必需的.
I've removed some elements from your original snippet that seemd to mess up things. I've also ignored the dash elements since they're not necessary to produce a minimal reproducible example.
代码:
#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()
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