添加数据帧时从数据帧中删除列表

Question

开始于：

import pandas as pd

lis1= [['apples'],['bananas','oranges','cinnamon'],['pears','juice']]
lis2= [['john'],['stacy'],['ron']]

pd.DataFrame({'fruits':lis1,'users':lis2})

                         fruits    users
0                      [apples]   [john]
1  [bananas, oranges, cinnamon]  [stacy]
2                [pears, juice]    [ron]

最后我想说：

lis3= ['apples','bananas','oranges','cinnamon','pears','juice']
lis4= ['john','stacy','stacy','stacy','ron','ron']

pd.DataFrame({'fruits': lis3, 'users':lis4})

     fruits  users
0    apples   john
1   bananas  stacy
2   oranges  stacy
3  cinnamon  stacy
4     pears    ron
5     juice    ron

首先，我需要创建一个新的dataframe，其中每个项都位于自己的行中。其次，name变量需要根据“水果”的数量进行重复。看看这个例子，约翰有一个水果，而斯泰西有5个水果——所以在用户名下，斯泰西必须重复5次

Answer 1

假设lis1和lis2具有相同数量的元素，则可以在压缩列表后使用列表理解来实现这一点

pd.DataFrame(
  [{'fruit':F, 'users':U} for (f, u) in zip(lis1, lis2) for F in f for U in u]
)

下面的代码生成以下输出：

      fruit    users
0    apples     john
1   bananas    stacy
2   oranges    stacy
3  cinnamon    stacy
4     pears      ron
5     juice      ron

Answer 2

itertools

from itertools import chain, product, starmap

pd.DataFrame(
    [*chain(*starmap(product, zip(df.fruits, df.users)))],
    columns=df.columns
)

     fruits  users
0    apples   john
1   bananas  stacy
2   oranges  stacy
3  cinnamon  stacy
4     pears    ron
5     juice    ron

---

如果您只有2列，这也适用

pd.DataFrame(
    [*chain(*starmap(product, zip(*map(df.get, df))))],
    columns=df.columns
)

---

generator

def f(z):
  for A, B in z:
    for a in A:
      for b in B:
        yield (a, b)

pd.DataFrame([*f(zip(df.fruits, df.users))], columns=df.columns)

     fruits  users
0    apples   john
1   bananas  stacy
2   oranges  stacy
3  cinnamon  stacy
4     pears    ron
5     juice    ron

Answer 3

下面是一个包含大量堆叠和拆垛的解决方案：

开始于：

>>> df
                         fruits    users
0                      [apples]   [john]
1  [bananas, oranges, cinnamon]  [stacy]
2                [pears, juice]    [ron]

用途：

final = (df.stack().apply(pd.Series)
         .stack(0).unstack(1)
         .ffill()
         .reset_index(drop=True))

>>> final
     fruits  users
0    apples   john
1   bananas  stacy
2   oranges  stacy
3  cinnamon  stacy
4     pears    ron
5     juice    ron