排序累积图 [英] Sorted cumulative plots

问题描述

如何在numpy/matplotlib或Pandas中获得排序的累积图?

How can I get sorted cumulative plots in numpy/matplotlib or Pandas?

让我用一个例子来解释一下.假设我们有以下数据:

Let me explain this with an example. Say we have the following data:

number_of_items_sold_per_store = [10, 6, 90, 5, 102, 10, 6, 50, 85, 1, 2, 3, 6]

我们想绘制一个图表，对于给定的(x，y)值，其读取方式为:销售量最高的%X个商店销售的%Y个商品.也就是说，它显示数据如下:

We want to plot a chart that, for a given (x,y) value is read as: the top %X selling stores sold %Y items. That is, it displays the data as follows:

                             

                             

最畅销商店位于左侧(即地块的斜率单调减小).我该如何在numpy或Pandas中执行此操作? (即假设以上是系列).

where the best selling stores are to the left (i.e. the slope of the plot decreases monotonically). How can I do this in numpy or Pandas ? (i.e. assuming the above is a Series).

推荐答案

假设您希望表现最好的商店排在首位:

Assuming that you want the best performing stores to come first:

import numpy as np
import matplotlib.pyplot as plt

number_of_items_sold_per_store = [10, 6, 90, 5, 102, 10, 6, 50, 85, 1, 2, 3, 6]

ar = sorted(number_of_items_sold_per_store,reverse=True)
y = np.cumsum(ar).astype("float32")

#normalise to a percentage
y/=y.max()
y*=100.

#prepend a 0 to y as zero stores have zero items
y = np.hstack((0,y))

#get cumulative percentage of stores
x = np.linspace(0,100,y.size)

#plot
plt.plot(x,y)
plt.show()

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