pandas 按照特定顺序输出的实现代码

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。

## 构造 pd.DataFrame

patient_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()

## output

week

friday 2

monday 3

saturday 1

thursday 2

tuesday 4

wednesday 3

Name: 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]

## output

week

monday 3

tuesday 4

wednesday 3

thursday 2

friday 2

saturday 1

Name: patient_id, dtype: int64

作图效果如下

test.groupby('week')['patient_id'].count().plot(kind='bar');

ind = ['monday','tuesday','wednesday','thursday','friday','saturday']

test.groupby('week')['patient_id'].count()[ind].plot(kind='bar');

总结

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