Plotly:如何绘制累积的“步骤"；直方图?

2022-01-21 00:00:00 python plotly histogram plotly-python

问题描述

我试图在 python 中使用 Plotly 绘制累积直方图，但让它看起来像步骤"，即没有颜色的条形图，只显示顶线.像这样的:

I am trying to plot a cumulative histogram using Plotly in python, but make it look like "steps", i.e. bars with no color and only the top line is displayed. Something like this:

基本上，我正在尝试重现以下 matplotlib 代码的行为:

Basically, I'm trying to reproduce the behavior of the following matplotlib code:

import matplotlib.pyplot as plt
plt.hist(x, cumulative=True, histtype='step')

到目前为止，我能做的最好的事情是:

So far, the best I've been able to do is:

import plotly.graph_objs as go
from plotly.offline import iplot
h = go.Histogram(x=x,
                         cumulative=dict(enabled=True),
                         marker=dict(color="rgba(0,0,0,0)",
                                     line=dict(color="red", width=1)))
iplot([h])

结果如下:

那么有什么诀窍呢?

解决方案

如果您愿意在绘制数据之前处理分箱和累积，您可以使用 go.线的 shape 属性设置为 'hvh' 的散布 对象.

If you're willing to handle the binning and accumulation before you plot the data, you can use a go.Scatter object with the shape property of the line set to 'hvh'.

剧情:

代码: Jupyter Notebook 的设置

Code: Setup for a Jupyter Notebook

#imports
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot

import numpy as np
import pandas as pd

# qtconsole for debugging
#%qtconsole -- style vim

# Notebook settings
init_notebook_mode(connected=True)

# Some sample data
x = np.random.normal(50, 5, 500)
binned = np.histogram(x, bins=25, density=True)
plot_y = np.cumsum(binned[0])

# Line
trace1 = go.Scatter(
    x=binned[1],
    y=plot_y,
    mode='lines',
    name="X",
    hoverinfo='all',
    line=dict(color = 'rgb(1255, 0, 0)', shape='hvh'
    )
)

data = [trace1]

# Layout
layout = dict(title = 'Binned data from normal distribution',
    legend=dict(
        y=0.5,
        traceorder='reversed',
        font=dict(
            size=16
        )
    )
)

# Make figure
fig = dict(data=data, layout=layout)

# Plot
iplot(fig, filename='line-shapes')

我希望这是你可以使用的东西！

I hope this is something you can use!

如果没有，请随时告诉我.

Don't hesitate to let me know if not.

一些细节:

数据样本是使用 np.random.normal() 制作的.x 是平均值 = 50、sigma = 5 和 500 个观测值的采样正态分布.然后使用返回两个数组的 np.histogram() 将 x 放入 50 个 bin 中.这些用作绘图的数据源.

The data sample is made using np.random.normal(). x is a sampled normal distribution with mean = 50, sigma = 5 and 500 observations. x is then put in 50 bins using np.histogram() which returns two arrays. These are used as data source for the plot.

可能的替代方法:

我还尝试将您的代码段与一些随机样本数据一起使用，并在您的 line=dict(color="red", width=1)shape='hvh'>.但这似乎不起作用.我还考虑过修改 go.Histogram() 的布局，以便只绘制条形的顶线，但我认为这是不可能的.

I also tried using your snippet with some random sample data and include shape='hvh' in your line=dict(color="red", width=1). That did not seem to work though. I also considered modifying the layout of your go.Histogram() so that only the top line of the bars were plotted, but I don't think it's possible.

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