Question

我有以下数据框：

network   date       count2    count3  user2     user3 
3         20170721   [6, 7]    [1,3]   [57,88]   [47,58] 
4         20170721   [6]       []      [12]      []
43        20170721   []        [7,2]   []        [57,62]

我希望每行拆分列表但计数和用户必须对应：

network   date       count2   count3  user2    user3 
3         20170727   6       Nan      57       Nan
3         20170727   7       Nan      88       Nan
3         20170727   Nan     1        Nan      47
3         20170727   Nan     3        Nan      58
4         20170727   6       Nan      12       Nan
43        20170727   Nan     7        Nan      57
43        20170727   Nan     2        Nan      62

我怎样才能快速完成？用户列表实际上很长（超过50k条目）。谢谢！

Answer 1

你可以做到这一点，并在没有额外NaN的情况下实现你正在寻找的结果。

df = pd.DataFrame({'network':[3,4,43],'date':['20170721']*3,
                   'count2':[[6,7],[6],[]],
                   'count3':[[1,3],[],[7,2]],
                   'user2':[[57,88],[12],[]],
                   'user3':[[47,58],[],[57,62]]})

df = df.set_index(['network','date'])

(df.apply(lambda x: pd.DataFrame(x.tolist(),index=x.index)
                      .stack()
                      .rename(x.name))
   .reset_index())

输出：

   network      date  level_2  level_0  count2  count3  user2  user3
0        3  20170721        0      0.0     6.0     1.0   57.0   47.0
1        3  20170721        1      NaN     7.0     3.0   88.0   58.0
2        4  20170721        0      1.0     6.0     NaN   12.0    NaN
3       43  20170721        0      2.0     NaN     7.0    NaN   57.0
4       43  20170721        1      NaN     NaN     2.0    NaN   62.0

python将多个列表转换为某些列表的行

1 个答案: