df.groupby() 之后按照特定顺序输出，方便后续作图，或者跟其他df对比作图。
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
|
## 构造 pd.dataframepatient_id = ['71835318256532', '87791375711', '66979212649388', '46569922967175', '998612492555522', '982293214194', '89981833848', '17912315786975', '4683495482494', '1484143378533', '56866972273357', '7796319285658', '414462476158336', '449519578512573', '61826664459895']week = ['tuesday', 'tuesday', 'wednesday', 'monday', 'tuesday', 'monday', 'friday', 'tuesday', 'monday', 'friday', 'saturday', 'thursday', 'wednesday', 'thursday', 'wednesday']d = {'patient_id': patient_id, 'week':week}test = pd.dataframe(data=d)## 聚类计数test.groupby('week')['patient_id'].count()## outputweekfriday 2monday 3saturday 1thursday 2tuesday 4wednesday 3name: patient_id, dtype: int64## 按照特定顺序输出ind = ['monday','tuesday','wednesday','thursday','friday','saturday']test.groupby('week')['patient_id'].count()[ind]## outputweekmonday 3tuesday 4wednesday 3thursday 2friday 2saturday 1name: patient_id, dtype: int64 |
作图效果如下
|
1
|
test.groupby('week')['patient_id'].count().plot(kind='bar'); |
|
1
2
|
ind = ['monday','tuesday','wednesday','thursday','friday','saturday']test.groupby('week')['patient_id'].count()[ind].plot(kind='bar'); |
总结
以上所述是小编给大家介绍的pandas 按照特定顺序输出的实现代码，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对服务器之家网站的支持！
原文链接：https://blog.csdn.net/Guo_ya_nan/article/details/80989067
