转换 pandas “成对阵列系列"到“两栏式DataFrame"? [英] Convert a pandas "Series of pair arrays" to a "two-column DataFrame"?

问题描述

我有一个Pandas系列，它由成对的阵列组成:

I have a Pandas Series that consists of arrays of pairs:

In [177]: pair_arrays
Out[177]: 
15192     [[1, 9], [2, 14], [4, 1], [5, 36], [6, 8], [7,...
16012     [[0, 107], [1, 42], [2, 22], [3, 59], [4, 117]...
17523     [[0, 44], [1, 36], [2, 43], [3, 28], [4, 52], ...
...

我想将其重塑为具有两列"x"和"y"的数据框，其形状类似于:

I would like to reshape that into a dataframe with two columns, 'x' and 'y', which has a shape similar to:

In [179]: pd.DataFrame([{'x':1, 'y':42}, {'x':4, 'y':12}], columns=['x', 'y'])
Out[179]: 
   x   y
0  1  42
1  4  12
...

我该怎么做?

推荐答案

假定系列中的每个元素都是对的数组，并且每个对都是一个序列，这应该可以工作:

Assuming that each element in the series is an array of pairs, and each pair is a sequence, this should work:

pair_df = pd.DataFrame(np.vstack(pair_arrays.values), columns=['x','y'])

关键是熊猫不知道如何使用对象数组.因此，我在这里所做的就是将其转换为对象数组的numpy数组.然后，我将堆叠对象数组，这将为您提供2D整数数组，然后将其转换回DataFrame.

The key point is that pandas doesn't know how to work with object arrays. So what I am doing here is converting it to a numpy array of object arrays. Then I am stacking the object arrays, which gets you a 2D integer array, and then converting it back to a DataFrame.

从技术上讲，您当前不需要使用values方法来显式转换为numpy数组，但是我认为这更清晰，并且从长期来看可能更安全.

Technically you don't currently need to use the values method to explicitly convert to a numpy array, but I think that is clearer and potentially safer long-term.

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