python - 将 Pandas 数据框行拆分为多行

Question

我有一个 pandas 时间序列，例如:

df = pd.DataFrame(
    {
        "IDs": [
            ["A", "B"],
            ["A", "B", "A", "C"],
            ["A", "B", "A", "D", "C", "D"],
        ],
        "distance": [[1], [1.1, 2.8], [1, 3, 0.5]],
    },
    index=[
        pd.to_datetime("2022-01-01 12:00:00"),
        pd.to_datetime("2022-01-01 12:00:01"),
        pd.to_datetime("2022-01-01 12:00:02"),
    ],
)

这会产生:

                     IDs    distance
2022-01-01 12:00:00 [A, B]  [1]
2022-01-01 12:00:01 [A, B, A, C]    [1.1, 2.8]
2022-01-01 12:00:02 [A, B, A, D, C, D]  [1, 3, 0.5]

我想拆分行，以便每一行只包含到一对的距离，例如:

                     IDs    distance
2022-01-01 12:00:00 [A, B]  1.0
2022-01-01 12:00:01 [A, B]  1.1
2022-01-01 12:00:01 [A, C]  2.8
2022-01-01 12:00:02 [A, B]  1.0
2022-01-01 12:00:02 [A, D]  3.0
2022-01-01 12:00:02 [C, D]  0.5

执行此操作的最佳方法是什么？

作为引用，每一行 IDs 行始终是 2n 个元素的列表，其中 n 是相应 distance 行中的元素数。

Answer 1

IIUC，使用列表推导将 ID 按 2 为一组进行分组，然后是 explode两个 ID/距离列:

df['IDs'] = [[l[i:i+2] for i in range(0,len(l),2)] for l in df['IDs']]
df = df.explode(['IDs', 'distance'])

注意。这要求每行的 len(IDs) 是 len(distance) 的 2 倍!

输出:

                        IDs distance
2022-01-01 12:00:00  [A, B]        1
2022-01-01 12:00:01  [A, B]      1.1
2022-01-01 12:00:01  [A, C]      2.8
2022-01-01 12:00:02  [A, B]        1
2022-01-01 12:00:02  [A, D]        3
2022-01-01 12:00:02  [C, D]      0.5