[英]How to set secondary x-axis and its range in plotly graph with subfigures?
does anyone know how to set a secondary x-axis and also its range in plotly?有谁知道如何设置辅助 x 轴及其在 plotly 中的范围?
I am trying to show a vertical histogram here but it is currently still too small我试图在这里显示一个垂直直方图,但它目前仍然太小
import pandas as pd import numpy as np import plotly.graph_objects as go from plotly.subplots import make_subplots from plotly.graph_objs.layout import YAxis,XAxis,Margin x1 = np.linspace(0, 4, 41) y1 = (x1-2)**3+2 y2 = x1*0+2 x1_sample = np.random.normal(2,0.3,5000) y1_sample = (x1_sample-2)**3+2 data = np.column_stack((x1_sample, y1_sample)) df_hist = pd.DataFrame(data = data, columns = ['x1_sample', 'y1_sample']) fig = make_subplots(rows=1, cols=2, specs = [[{"secondary_y": True}, {"secondary_y": True}]], horizontal_spacing=0.2) # Subplot 1 ## Line fig.update_yaxes(range = [0, 4], dtick = 1, secondary_y=False) fig.add_trace( go.Scatter(x = x1, y = y1, mode='lines'), row = 1, col = 1 ) fig.add_trace( go.Scatter(x = x1, y = y2, mode = 'lines'), row = 1, col = 1 ) ## Histogram fig.update_yaxes(range = [0, 0.5], dtick = 0.1, secondary_y=True) fig.add_trace( go.Histogram(x = df_hist['x1_sample'], histnorm='probability', nbinsx=40), secondary_y=True, row = 1, col = 1 ) fig.add_trace( go.Histogram(y = df_hist['y1_sample'], histnorm='probability', nbinsy=40), row = 1, col = 1 )
To get what you need in your example, just add the following lines to your setup:要在示例中获得所需的内容,只需将以下行添加到您的设置中:
fig.update_layout(xaxis2= {'anchor': 'y', 'overlaying': 'x', 'side': 'top'})
fig.data[3].update(xaxis='x2')
fig.update_layout(xaxis2_range=[-0,0.6])
Line 1 sets up a secondary x-axis, while line 2 assigns a trace to it.第 1 行设置了一个辅助 x 轴,而第 2 行为其分配了一条迹线。 I'm assuming
fig.data[3]
is the correct trace but you can check that for yourself.我假设
fig.data[3]
是正确的跟踪,但您可以自己检查。 Line 3, unsuprisingly, sets the range of the secondary x-axis.不出所料,第 3 行设置了辅助 x 轴的范围。
import numpy as np
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from plotly.graph_objs.layout import YAxis,XAxis,Margin
x1 = np.linspace(0, 4, 41)
y1 = (x1-2)**3+2
y2 = x1*0+2
x1_sample = np.random.normal(2,0.3,5000)
y1_sample = (x1_sample-2)**3+2
data = np.column_stack((x1_sample, y1_sample))
df_hist = pd.DataFrame(data = data, columns = ['x1_sample', 'y1_sample'])
fig = make_subplots(rows=1, cols=2, specs = [[{"secondary_y": True}, {"secondary_y": True}]],
horizontal_spacing=0.2,
shared_xaxes = False)
# Subplot 1
## Line
fig.update_yaxes(range = [0, 4], dtick = 1, secondary_y=False)
fig.add_trace(
go.Scatter(x = x1 , y = y1, mode='lines'),
row = 1, col = 1
)
fig.add_trace(
go.Scatter(x = x1, y = y2, mode = 'lines'),
row = 1, col = 1
)
## Histogram
fig.update_yaxes(range = [0, 0.5], dtick = 0.1, secondary_y=True)
fig.add_trace(
go.Histogram(x = df_hist['x1_sample'], histnorm='probability', nbinsx=40),
secondary_y=True,
row = 1, col = 1
)
fig.add_trace(
go.Histogram(y = df_hist['y1_sample'], histnorm='probability', nbinsy=40),
row = 1, col = 1
)
fig.update_layout(xaxis2= {'anchor': 'y', 'overlaying': 'x', 'side': 'top'})
fig.data[3].update(xaxis='x2')
fig.update_layout(xaxis2_range=[-0,0.6])
fig.show()
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