python - Pandas 根据其他列中的值创建新列

Question

假设我有以下 DataFrame:

dfff = pd.DataFrame({"name":[["a","b","c","d"]], "value":[[["a","aa"],["b","bb"],["c","cc"],["d","dd"]]]})


    name                         value
[a, b, c, d]    [[a, aa], [b, bb], [c, cc], [d, dd]]

从此我想要类似的东西:

   a       b      c        d
[a, aa] [b, bb] [c, cc] [d, dd]

对于单行，这段代码可以工作，但如果有多行，则不行:

for i in range(len(dfff)):
    for num, val in enumerate(dfff.name[i]):
        dfff[val] = [dfff.value[i][num]]
dfff.drop(["name","value"], axis = 1, inplace = True)

我如何实现这是 Pandas ？非常感谢

编辑:多行表示例:

    name                         value
0   [a, b, c, d]    [[a, aa], [b, bb], [c, cc], [d, dd]]
1   [c, d, e]       [[c, cc], [d, dd], [e, ee]]

它应该变成:

   a       b      c        d       e
[a, aa] [b, bb] [c, cc] [d, dd]   None
  None   None   [c, cc] [d, dd]   [e, ee]

Answer 1

我们可以在列表理解中zip列name和value，然后迭代压缩的值以及每个名称-值pair 创建对应的record/dict

pd.DataFrame([dict(zip(*pair)) for pair in zip(df['name'], df['value'])])

---

         a        b        c        d        e
0  [a, aa]  [b, bb]  [c, cc]  [d, dd]      NaN
1      NaN      NaN  [c, cc]  [d, dd]  [e, ee]