情节如何在相同的y轴上用不同的X阵列绘制多条线

发布于 2025-01-21 18:27:14 字数 537 浏览 0 评论 0原文

我尝试使用Python中的绘图来绘制几行在同一图上具有自己的X值。

x1 = [1, 3, 5, 7, 9]
y1 = np.random.random(5)

x2 = [2, 4, 6, 8, 10]
y2 = np.random.random(5)

我想将其绘制在1到10的一个X轴上。
stackoverflow上的所有答案（例如 this ）用熊猫数据框来描述解决方案，其中所有线（y1和y2）具有与每条线相对应的X值的相同数组。但是，在我的情况下，Y1和Y2具有相应的X值不同（尽管在相同的单元中）。

我该怎么做才能在情节中制作这样的情节？

原文

I try to use plotly in python to plot several lines having their own X-values on the same graph for example.

x1 = [1, 3, 5, 7, 9]
y1 = np.random.random(5)

x2 = [2, 4, 6, 8, 10]
y2 = np.random.random(5)

I want to plot this on the one x-axis from 1 to 10.
All answers on StackOverFlow (like this) describe the solution with a pandas dataframe where all lines (y1 and y2) have the same array of x-values corresponding to each line. However, in my case y1 and y2 have different (though in the same units) corresponding x-values.

What can I do to make such a plot in plotly?

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╭⌒浅淡时光〆 2025-01-28 18:27:14

当您没有数据框架时，我认为最简单的方法是使用plotly.graph_objects。

import plotly.graph_objects as go

x1 = [1, 3, 5, 7, 9]
y1 = np.random.random(5)
x2 = [2, 4, 6, 8, 10]
y2 = np.random.random(5)

f1 = go.Figure(
    data = [
        go.Scatter(x=x1, y=y1, name="first"),
        go.Scatter(x=x2, y=y2, name="second"),
    ],
    layout = {"xaxis": {"title": "x axis"}, "yaxis": {"title": "y axis"}, "title": "My title"}
)
f1

您也可以使用plotly.express模块，但是它需要更多代码来设置传说上的名称。

在此文档页面。

When you don't have a dataframe, I argue that the easiest way is to use plotly.graph_objects.

import plotly.graph_objects as go

x1 = [1, 3, 5, 7, 9]
y1 = np.random.random(5)
x2 = [2, 4, 6, 8, 10]
y2 = np.random.random(5)

f1 = go.Figure(
    data = [
        go.Scatter(x=x1, y=y1, name="first"),
        go.Scatter(x=x2, y=y2, name="second"),
    ],
    layout = {"xaxis": {"title": "x axis"}, "yaxis": {"title": "y axis"}, "title": "My title"}
)
f1

You can also use the plotly.express module, however it requires a bit more code to set the names on the legends.

Learn more at this documentation page.

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┈┾☆殇 2025-01-28 18:27:14

只需在示例数据上使用一个 little 数据争吵，您就可以使用此行：

fig = px.line(df, x = 'x', y = 'y', color = 'name', markers = True)

a href =“ https://i.sstatic.net/naius.png “ rel =“ nofollow noreferrer”> “在此处输入映像说明”

争吵只是在您的两个数据范围内构建两个数据范围categories并将它们堆放到所谓的绘制表达精美的长形式。与所谓的广泛形式数据相反，不同类别的观察数是否不同。

完成代码：

import plotly.express as px
import pandas as pd
import numpy as np

x1 = [1, 3, 5, 7, 9]
y1 = np.random.random(5)

x2 = [2, 4, 6, 8, 10]
y2 = np.random.random(5)

df1 = pd.DataFrame({'name': ['1']*len(x1),
                    'x': x1,
                    'y': y1})

df2 = pd.DataFrame({'name': ['2']*len(x2),
                    'x': x2,
                    'y': y2})

df = pd.concat([df1, df2])

fig = px.line(df, x = 'x', y = 'y', color = 'name', markers = True)
fig.show()

With just a little bit of data wrangling on your example data, you can just use this single line:

fig = px.line(df, x = 'x', y = 'y', color = 'name', markers = True)

And get this:

The wrangling is just building two dataframes out of your categegories and stacking them into a so-called long form which plotly express handles beautifully. Contrary to so-called wide form data, it won't matter if the different categories have a different number of observations.

Complete code:

import plotly.express as px
import pandas as pd
import numpy as np

x1 = [1, 3, 5, 7, 9]
y1 = np.random.random(5)

x2 = [2, 4, 6, 8, 10]
y2 = np.random.random(5)

df1 = pd.DataFrame({'name': ['1']*len(x1),
                    'x': x1,
                    'y': y1})

df2 = pd.DataFrame({'name': ['2']*len(x2),
                    'x': x2,
                    'y': y2})

df = pd.concat([df1, df2])

fig = px.line(df, x = 'x', y = 'y', color = 'name', markers = True)
fig.show()

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