如何将计数添加到直方图?

本文介绍了如何将计数添加到直方图?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我想将直方图的计数数据添加到matplotlib中的绘图中.这是我的数据；

I want to add the counts data of histogram to the plot in matplotlib. Here is my data;

import matplotlib.pyplot as plt data = [['B', 1], ['C', 2], ['A', 3],['A', 4], ['B', 5], ['B', 6],['A', 7], ['B', 8], ['C', 9],['D',10]] df = pd.DataFrame(data, columns = ['Name', 'Count']) plt.hist(df['Name']) plt.show()

结果是这样的； 结果1

我尝试使用plt.text和value_counts()，但是它们的排序方式有所不同...

I tried to use plt.text and value_counts() but their sorting are different...

import matplotlib.pyplot as plt data = [['B', 1], ['C', 2], ['A', 3],['A', 4], ['B', 5], ['B', 6],['A', 7], ['B', 8], ['C', 9],['D',10]] df = pd.DataFrame(data, columns = ['Name', 'Count']) xvals = np.arange(len(df['Name'].value_counts())) yvals = list(df['Name'].value_counts()) for i in range(len(df['Name'].value_counts())): plt.text(x=xvals[i], y=yvals[i],s=df['Name'].value_counts(sort=False)[i]) plt.hist(df['Name']) plt.show()

所以，我得到这样的结果； 结果2

So, I get a result like this; result2

我认为应该没那么困难，但是我找不到任何解决方案.

I think it mustn't be so difficult but I can't find any solution.

推荐答案

您可以尝试执行以下操作:

You can try something like this:

hist返回计数，垃圾箱和补丁. patches是矩形的列表.然后，您可以使用面片矩形的计数和坐标来注释轴.

hist returns counts, bins and patches. patches is a list of rectangles. Then you can annotate the axis using the count and coordinates of the patch rectangles.

import numpy as np import matplotlib.pyplot as plt # generate some random data x = np.random.randn(10000) x = x * 100 x = x.astype(np.int) # plot the histogram of the data bins = np.arange(-300,300,20) fig = plt.figure(figsize=(15,4)) ax = plt.gca() counts, _, patches = ax.hist(x, bins=bins,edgecolor='r') for count, patch in zip(counts,patches): ax.annotate(str(int(count)), xy=(patch.get_x(), patch.get_height())) plt.show()