Question

以下是我的例子：

TypeError                                 Traceback (most recent call last)
<ipython-input-48-228f7f5e9d1e> in <module>()
      1 test_list = ['a', 'b', 'b', 'c']
----> 2 plt.hist(test_list)
      3 plt.show()

C:\Anaconda3\lib\site-packages\matplotlib\pyplot.py in hist(x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, hold, data, **kwargs)
   2956                       histtype=histtype, align=align, orientation=orientation,
   2957                       rwidth=rwidth, log=log, color=color, label=label,
-> 2958                       stacked=stacked, data=data, **kwargs)
   2959     finally:
   2960         ax.hold(washold)

C:\Anaconda3\lib\site-packages\matplotlib\__init__.py in inner(ax, *args, **kwargs)
   1809                     warnings.warn(msg % (label_namer, func.__name__),
   1810                                   RuntimeWarning, stacklevel=2)
-> 1811             return func(ax, *args, **kwargs)
   1812         pre_doc = inner.__doc__
   1813         if pre_doc is None:

C:\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
   5993             xmax = -np.inf
   5994             for xi in x:
-> 5995                 if len(xi) > 0:
   5996                     xmin = min(xmin, xi.min())
   5997                     xmax = max(xmax, xi.max())

TypeError: len() of unsized object

它会生成以下错误消息：

{{1}}

我只是简单地搜索谷歌，但看起来我无法在matplotlib中绘制分类变量的直方图。

任何人都可以确认吗？

Answer 1

当然可以在matplotlib中创建分类数据的直方图。正如this link建议的那样，但也正如matplotlib demo中所建议的那样，只需为此目的使用条形图。

import matplotlib.pyplot as plt
import numpy as np

test_list = ['a', 'b', 'b', 'c', "d", "b"]
histdic = {x: test_list.count(x) for x in test_list}
x = []; y=[]
for key, value in histdic.iteritems():
    x.append(key)
    y.append(value)

plt.figure()
barwidth= 0.8
plt.bar(np.arange(len(y)),y, barwidth, color='r')
plt.gca().set_xticks(np.arange(len(y))+barwidth/2.)
plt.gca().set_xticklabels(x)
plt.show()

由于这个是一个直方图，而是用matplotlib创建的，所以说＆＃34;无法绘制直方图是绝对错误的对于matplotlib＆＃34; 中的分类变量。

Answer 2

尝试使用以下代码：

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

cats = np.array([l for l in "ABCD"], dtype=str)
cats = np.random.ch`enter code here`oice(cats, 100, p=[0.3, 0.1, 0.4, 0.2])

res = np.random.choice(np.arange(1,7), 100, p=[0.2, 0.1, 0.08, 0.16,0.26,0.2])
df = pd.DataFrame({"Category":cats, "Result":res})
df2 = df.groupby(["Category", "Result"]).size().reset_index(name='Count')


df3 = pd.pivot_table(df2,  values='Count',  columns=['Result'],  index = "Category",
                         aggfunc=np.sum,  fill_value=0)
df4 = pd.pivot_table(df2,  values='Count',  columns=['Category'],  index = "Result",
                         aggfunc=np.sum,  fill_value=0)

fig, ax = plt.subplots(1,2, figsize=(10,4))
df3.plot(kind="bar", ax=ax[0])
df4.plot(kind="bar", ax=ax[1]) 

plt.show()

Matplotlib无法绘制分类值

2 个答案: