numpy数组的元素作为具有相同索引的自己的 pandas 行 [英] Elements of numpy array as own pandas row with same index

问题描述

我有一个带有numpy数组作为列中值的pandas DataFrame.我想将每个元素转换为具有相同日期的行:

I have a pandas DataFrame with numpy arrays as values in a column. I would like to turn each element to a row with the same date:

我的DataFrame看起来像这样:

My DataFrame looks like this:

    date    website+
0       2014-11-26  [A]
238     2015-12-20  [B, C]
297     2016-02-17  [D]
303     2016-02-23  [E, F, G]

我想要:

       date     website+
    0       2014-11-26  [A]
    238     2015-12-20  [B]
            2015-12-20  [C]
    297     2016-02-17  [D]
    303     2016-02-23  [E]
            2016-02-23  [F]
            2016-02-23  [G]

只要日期保持不变，索引就不重要.我找到了一种将每个条目都变成一列的解决方案，但这并不是我想要的.

The index is not important as long as the date stays the same. I have found a solution to turn each entry into a column, but thats not exactly what I want.

推荐答案

如果第一列已在索引中，则可以使用以下内容:

If your first column is already in index, then you can use the following:

df.set_index('date', append=True)['website+']\
  .apply(pd.Series).stack().reset_index(level=-1, drop=True)\
  .to_frame(name='website+')

输出:

               website+
    date               
0   2014-11-26        A
238 2015-12-20        B
    2015-12-20        C
297 2016-02-17        D
303 2016-02-23        E
    2016-02-23        F
    2016-02-23        G

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