Question

所以，我想知道如何用条件划分一列。我的想法是研究用户的活动，但是为此，我需要提出一个条件。我有数据框：

df = pd.DataFrame({'User': ["juan","juan","juan","juan","petter","petter","petter","petter","petter","petter","petter","petter","ana","ana","ana","ana","raul","raul","raul","raul"],
               'time': ["2/1/2019","3/1/2019","4/1/2019","6/1/2019","2/1/2019","5/1/2019","6/1/2019","10/1/2019","11/1/2019","12/1/2019","13/1/2019","14/1/2019","8/1/2019","10/1/2019","15/1/2019","20/1/2019","15/1/2019","17/1/2019","18/1/2019","19/1/2019"],
                'activity': ["fly", "hotel","car","jump","fly", "hotel","jump","car","fly", "car","hotel","car","car", "hotl","car","hotel","fly", "hotel","car","car"],
              '%timeper_user': ["4 days","4 days","4 days","4 days","8 days","8 days","8 days","8 days","3 days","3 days","3 days","3 days","12 days","12 days","12 days","12 days","4 days","4 days","4 days","4 days"]})

如您所见，

每个用户都有一个列（时间），每个用户有另一个列（％timeper_user）。然后是一列（活动），即每个用户在一段时间内执行的活动。这个想法是将每个活动放在不同的列中进行“条件拆分”。行为1，行为2，行为3，行为3。但是，当用户执行时间以外的活动（时间+ timeper_user的百分比）时，请将活动放在不同的列中，例如：Act21，Act 22，Act 23，Act24我希望这样：

df2 = pd.DataFrame({'User': ["juan","petter","ana","raul"],
              "act1":["fly","fly","car","fly"],
              "act2":["hotel","hotel","hotel","hotel"],
              "act3":["car","jump","car","car"],
              "act4":["jump","car","hotel","car"],
              "actn":["","","",""],
              "act21":["","fly","",""],
              "act22":["","car","",""],
              "act23":["","hotel","",""],
              "act24":["","car","",""]})

（DF2）是我想要的输出查看用户Petter超过时间（2/1/2019 + 8天）= 10/1/2019。因此，从11/1/2019起，活动将放置在Act21，Act22，Act23，Act24中。我有很多用户，所以我不知道如何执行执行此操作并接受全部操作的功能（逐个用户）。如果您能帮助我，我将非常感谢。谢谢

Answer 1

这个想法是。如果用户在范围（时间+每个用户的时间百分比）之间进行事件，则表示所有活动都属于内部，请输入活动范围1（act1，Act12，Act13，Act 14）。如果日期较大，则表示用户将输入活动2（act21，act22，act23，act24）。简单来说...如果彼得从美国去马德里，他可能会去旅馆，租车，然后试乘飞机。但是当他返回美国时，在附近，佩特可能会购买第二次飞行（这将进入范围活动2（动作21，act22，Act23，act24）。如果您运行df ...是我拥有的数据框。。和df2是我要制作的数据

如何根据条件拆分列

1 个答案: