直接在图形上可视化 matplotlib 直方图 bin 计数

Question

请我想我有一个简单的问题，但我看不到任何有用的博客来展示如何实现这一目标。我有一个名为“series”的 python pandas 系列，我使用 series.hist() 来可视化直方图。我需要直接在图表上可视化每个 bin 的出现次数，但我找不到解决方案。

我如何才能在每个垃圾箱顶部看到一个标签，显示每个垃圾箱的出现次数？

准确地说，这是我的代码：

import matplotlib.pyplot as plt
your_bins=10
data = [df_5m_9_4pm.loc['2017-6']['sum_daily_cum_ret'].values]
plt.hist(data, binds = your_bins)
arr = plt.hist(data,bins = your_bins)
for i in range(your_bins):
    plt.text(arr[1][i],arr[0][i],str(arr[0][i]))

如果我只是打印变量“数据”，它是这样的：

[array([ 0.        ,  0.03099187, -0.00417244, ..., -0.00459067,
         0.0529476 , -0.0076605 ])]

如果我运行上面的代码，我会收到错误消息：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-97-917078981b1d> in <module>()
      2 your_bins=10
      3 data = [df_5m_9_4pm.loc['2017-6']['sum_daily_cum_ret'].values]
----> 4 plt.hist(data, binds = your_bins)
      5 arr = plt.hist(data,bins = your_bins)
      6 for i in range(your_bins):

~/anaconda3/lib/python3.6/site-packages/matplotlib/pyplot.py in hist(x, bins, range, density, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, normed, hold, data, **kwargs)
   3002                       histtype=histtype, align=align, orientation=orientation,
   3003                       rwidth=rwidth, log=log, color=color, label=label,
-> 3004                       stacked=stacked, normed=normed, data=data, **kwargs)
   3005     finally:
   3006         ax._hold = washold

~/anaconda3/lib/python3.6/site-packages/matplotlib/__init__.py in inner(ax, *args, **kwargs)
   1708                     warnings.warn(msg % (label_namer, func.__name__),
   1709                                   RuntimeWarning, stacklevel=2)
-> 1710             return func(ax, *args, **kwargs)
   1711         pre_doc = inner.__doc__
   1712         if pre_doc is None:

~/anaconda3/lib/python3.6/site-packages/matplotlib/axes/_axes.py in hist(***failed resolving arguments***)
   6205             # this will automatically overwrite bins,
   6206             # so that each histogram uses the same bins
-> 6207             m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
   6208             m = m.astype(float)  # causes problems later if it's an int
   6209             if mlast is None:

~/anaconda3/lib/python3.6/site-packages/numpy/lib/function_base.py in histogram(a, bins, range, normed, weights, density)
    665     if mn > mx:
    666         raise ValueError(
--> 667             'max must be larger than min in range parameter.')
    668     if not np.all(np.isfinite([mn, mx])):
    669         raise ValueError(

ValueError: max must be larger than min in range parameter.

Answer 1

尝试这个：

import matplotlib.pyplot as plt              
import numpy as np                                       


x = np.random.normal(size = 1000)                                         
counts, bins, patches = plt.hist(x, normed=True)
plt.ylabel('Probability')

# Label the raw counts and the percentages below the x-axis...
bin_centers = 0.5 * np.diff(bins) + bins[:-1]
for count, x in zip(counts, bin_centers):
    # Label the raw counts
    plt.annotate('{:.2f}'.format(count), xy=(x, 0), xycoords=('data', 'axes fraction'),
        xytext=(0, 18), textcoords='offset points', va='top', ha='center')

plt.show()

如果您想要原始出现而不是频率，只需删除normed=True并可能更改格式字符串。

我可能会补充说，你也可以解决这个问题，基本上只需复制侧边栏中链接的问题中的代码并更改(0, -18)为(0, 18).