绘制长度不均匀的分布图

Question

关注the plotly directions，我想绘制类似于以下代码的内容：

import plotly.plotly as py
import plotly.figure_factory as ff

import numpy as np

# Add histogram data
x1 = np.random.randn(200) - 2  
x2 = np.random.randn(200)  
x3 = np.random.randn(200) + 2  
x4 = np.random.randn(200) + 4  


# Group data together
hist_data = [x1, x2, x3, x4]

group_labels = ['Group 1', 'Group 2', 'Group 3', 'Group 4']

# Create distplot with custom bin_size
fig = ff.create_distplot(hist_data, group_labels, bin_size = [.1, .25, .5, 1])

# Plot!
py.iplot(fig, filename = 'Distplot with Multiple Bin Sizes')

但是，我有一个样本大小不均匀的真实世界数据集（即组1的计数与组2中的计数不同，等等）。此外，它是名称 - 值对格式。

这是一些虚拟数据来说明：

# Add histogram data
x1 = pd.DataFrame(np.random.randn(100))
x1['name'] = 'x1'

x2 = pd.DataFrame(np.random.randn(200) + 1)
x2['name'] = 'x2'

x3 = pd.DataFrame(np.random.randn(300) - 1)
x3['name'] = 'x3'

df = pd.concat([x1, x2, x3])
df = df.reset_index(drop = True)
df.columns = ['value', 'names'] 

df

如您所见，每个名称（x1，x2，x3）都有不同的计数，而“名称”列也是我想用作颜色的。

有谁知道如何在情节上策划这个？

在R中的FYI，它非常简单，我只需要调用ggplot，并在aes(fill = names)中。

任何帮助将不胜感激，谢谢！

Answer 1

您可以尝试对数据帧进行切片，然后将其放入Ploty中。

fig = ff.create_distplot([df[df.names == a].value for a in df.names.unique()], df.names.unique(), bin_size=[.1, .25, .5, 1])

import plotly
import pandas as pd
plotly.offline.init_notebook_mode()
x1 = pd.DataFrame(np.random.randn(100))
x1['name']='x1'

x2 = pd.DataFrame(np.random.randn(200)+1)
x2['name']='x2'

x3 = pd.DataFrame(np.random.randn(300)-1)
x3['name']='x3'

df=pd.concat([x1,x2,x3])
df=df.reset_index(drop=True)
df.columns = ['value','names'] 
fig = ff.create_distplot([df[df.names == a].value for a in df.names.unique()], df.names.unique(), bin_size=[.1, .25, .5, 1])
plotly.offline.iplot(fig, filename='Distplot with Multiple Bin Sizes')

Answer 2

example的plotly文档中的开箱即用，样本尺寸也不均匀：

#!/usr/bin/env python 

import plotly
import plotly.figure_factory as ff
plotly.offline.init_notebook_mode()
import numpy as np

# data with different sizes
x1 = np.random.randn(300)-2  
x2 = np.random.randn(200)  
x3 = np.random.randn(4000)+2  
x4 = np.random.randn(50)+4  

# Group data together
hist_data = [x1, x2, x3, x4]

# use custom names
group_labels = ['x1', 'x2', 'x3', 'x4']

# Create distplot with custom bin_size
fig = ff.create_distplot(hist_data, group_labels, bin_size=.2)

# change that if you don't want to plot offline
plotly.offline.plot(fig, filename='Distplot with Multiple Datasets')

上述脚本将产生以下结果：

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