装箱范围的 pandas 条形图 [英] Pandas bar plot with binned range

问题描述

是否有一种方法可以根据合并为预定义间隔的连续数据创建条形图?例如

Is there a way to create a bar plot from continuous data binned into predefined intervals? For example,

In[1]: df
Out[1]: 
0      0.729630
1      0.699620
2      0.710526
3      0.000000
4      0.831325
5      0.945312
6      0.665428
7      0.871845
8      0.848148
9      0.262500
10     0.694030
11     0.503759
12     0.985437
13     0.576271
14     0.819742
15     0.957627
16     0.814394
17     0.944649
18     0.911111
19     0.113333
20     0.585821
21     0.930131
22     0.347222
23     0.000000
24     0.987805
25     0.950570
26     0.341317
27     0.192771
28     0.320988
29     0.513834

231    0.342541
232    0.866279
233    0.900000
234    0.615385
235    0.880597
236    0.620690
237    0.984375
238    0.171429
239    0.792683
240    0.344828
241    0.288889
242    0.961686
243    0.094402
244    0.960526
245    1.000000
246    0.166667
247    0.373494
248    0.000000
249    0.839416
250    0.862745
251    0.589873
252    0.983871
253    0.751938
254    0.000000
255    0.594937
256    0.259615
257    0.459916
258    0.935065
259    0.969231
260    0.755814

，而不是简单的直方图:

and instead of a simple histogram:

df.hist()

我需要创建一个条形图，其中每个条形图都会计算预定义范围内的多个实例. 例如，下面的绘图应具有三个条形，其点数为:[0 0.35]，[0.35 0.7] [0.7 1.0]

I need to create a bar plot, where each bar will count a number of instances within a predefined range. For example, the following plot should have three bars with the number of points which fall into: [0 0.35], [0.35 0.7] [0.7 1.0]

编辑

非常感谢您的回答.另一个问题，如何订购垃圾桶? 例如，我得到以下结果:

Many thanks for your answers. Another question, how to order bins? For example, I get the following result:

In[349]: out.value_counts()
Out[349]:  
[0, 0.001]      104
(0.001, 0.1]     61
(0.1, 0.2]       32
(0.2, 0.3]       20
(0.3, 0.4]       18
(0.7, 0.8]        6
(0.4, 0.5]        6
(0.5, 0.6]        5
(0.6, 0.7]        4
(0.9, 1]          3
(0.8, 0.9]        2
(1, 1.001]        0

如您所见，最后三个垃圾箱没有排序.如何根据类别"或我的垃圾箱对数据框进行排序?

as you can see, the last three bins are not ordered. How to sort the data frame based on 'categories' or my bins?

编辑2

只需找到"reindex()"即可解决该问题:

Just found how to solve it, simply with 'reindex()':

In[355]: out.value_counts().reindex(out.cat.categories)
Out[355]: 
[0, 0.001]      104
(0.001, 0.1]     61
(0.1, 0.2]       32
(0.2, 0.3]       20
(0.3, 0.4]       18
(0.4, 0.5]        6
(0.5, 0.6]        5
(0.6, 0.7]        4
(0.7, 0.8]        6
(0.8, 0.9]        2
(0.9, 1]          3
(1, 1.001]        0

推荐答案

您可以使用

You can make use of pd.cut to partition the values into bins corresponding to each interval and then take each interval's total counts using pd.value_counts. Plot a bar graph later, additionally replace the X-axis tick labels with the category name to which that particular tick belongs.

out = pd.cut(s, bins=[0, 0.35, 0.7, 1], include_lowest=True)
ax = out.value_counts(sort=False).plot.bar(rot=0, color="b", figsize=(6,4))
ax.set_xticklabels([c[1:-1].replace(","," to") for c in out.cat.categories])
plt.show()

如果您希望将Y轴显示为相对百分比，请对频率计数进行归一化，然后将结果乘以100.

If you want the Y-axis to be displayed as relative percentages, normalize the frequency counts and multiply that result with 100.

out = pd.cut(s, bins=[0, 0.35, 0.7, 1], include_lowest=True)
out_norm = out.value_counts(sort=False, normalize=True).mul(100)
ax = out_norm.plot.bar(rot=0, color="b", figsize=(6,4))
ax.set_xticklabels([c[1:-1].replace(","," to") for c in out.cat.categories])
plt.ylabel("pct")
plt.show()

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