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.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
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
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武林站长站网站的支持!
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