python中apply后如何输出一个dataframe而不是一整个serices？

Question

def active_status(data):
    status = []
    for i in range(18):
        
        #若本月没有消费
        if data[i] == 0:
            if len(status) > 0:
                if status[i-1] == 'unreg':
                    status.append('unreg')
                else:
                    status.append('unactive')
            else:
                status.append('unreg')
        
        #若本月消费
        else:
            if len(status) == 0:
                status.append('new')
            else:
                if status[i-1] == 'unactive':
                    status.append('return')
                elif status[i-1] == 'unreg':
                    status.append('new')
                else:
                    status.append('active')
    return status



purchase_stats = df_purchase.apply(active_status,axis=1)
purchase_stats
#返回结果
user_id
1        [new, unactive, unactive, unactive, unactive, ...
2        [new, unactive, unactive, unactive, unactive, ...
3        [new, unactive, return, active, unactive, unac...
4        [new, unactive, unactive, unactive, unactive, ...
5        [new, active, unactive, return, active, active...
                               ...                        
23566    [unreg, unreg, new, unactive, unactive, unacti...
23567    [unreg, unreg, new, unactive, unactive, unacti...
23568    [unreg, unreg, new, active, unactive, unactive...
23569    [unreg, unreg, new, unactive, unactive, unacti...
23570    [unreg, unreg, new, unactive, unactive, unacti...
Length: 23570, dtype: object

df_purchase还是一个dataframe表格如下图（我的目的就是把下图的数字替换成一个个如"new"\"unreg"等的英文）：

 

Answer 1

对series再处理一下,构造成数据框。这样写，题主看看是不是能得到需要的结果。

purchase_stats = pd.DataFrame(df_purchase.apply(active_status, axis=1).tolist(), index=df_purchase.index, columns=df_purchase.columns)
print(purchase_stats)


month  1997-01-01  ... 1997-04-01
userid             ...
23566       unreg  ...   unactive
23577       unreg  ...   unactive
23588       unreg  ...     active
23589         new  ...     active