如何按条件拆分列

Question

所以，我想知道如何用条件来划分一列。我的想法是研究用户的活动，但为此我需要设置一个条件。 我有数据帧：

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"]})

正如您将看到的，每个用户都有一个列（time），每个用户都有另一个列（%timeper\u user）。然后是一个列（activity），它是每个用户在一段时间内执行的活动。我们的想法是做一个“条件分割”，将每个活动放在不同的列中。动作1，动作2，动作3，动作3。但是当用户在时间之外执行活动时（time+%timeper\u user），请将活动放在不同的列中，例如：Act21、act22、act23、Act24我希望它是这样的：

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）是我想要的输出吗 查看用户Petter超过时间（2/1/2019+8天）=10/1/2019。因此，从2019年11月1日起，活动被安排在Act21、Act22、Act23、Act24中。 我有很多用户，所以我不知道如何做一个函数来执行这一点，并采取所有（用户对用户）。如果你能帮助我，我将非常感激。谢谢

Answer 1

我的想法是。如果用户在范围（时间+每个用户的时间百分比）之间创建事件，则表示所有活动都属于活动范围1（act1、Act12、Act13、ACT14）。如果日期更大，则表示用户将输入activity2（act21、act22、act23、act24）。简单地说。。。如果佩特从美国去马德里，他可能会去酒店，租车，并尝试飞行。但在那里，当他回到美国，皮特可能会购买第二次飞行（这将进入范围活动2（第21幕，第22幕，第23幕，第24幕）。如果你运行df。。。是我的数据帧。。df2是我想要的数据