从长度不等的嵌套列表中创建 pandas 数据框 [英] Create a pandas dataframe from a nested lists of unequal lengths

问题描述

所以我有如下列表:

aa = ['aa1', 'aa2', 'aa3', 'aa4', 'aa5']
bb = ['bb1', 'bb2', 'bb3', 'bb4']
cc = ['cc1', 'cc2', 'cc3']

然后将其创建到嵌套列表中:

Which is then created into a nested list:

nest = [aa, bb, cc]

我要创建一个数据框，如下所示:

I want to create a dataframe as follows:

aa   bb   cc
aa1  bb1  cc1
aa2  bb2  cc2
aa3  bb3  cc3
aa4  bb4  nan
aa5  nan  nan

我尝试过:

pd.DataFrame(nest, columns=['aa', 'bb', cc'])

但是结果是，每个列表都被写成一行(而不是一列)

But results is such that, each list is being written as a row (as opposed to a column)

推荐答案

itertools中的zip_longest函数执行以下操作:

The zip_longest function from itertools does this:

>>> import itertools, pandas
>>> pandas.DataFrame((_ for _ in itertools.zip_longest(*nest)), columns=['aa', 'bb', 'cc'])
    aa    bb    cc
0  aa1   bb1   cc1
1  aa2   bb2   cc2
2  aa3   bb3   cc3
3  aa4   bb4  None
4  aa5  None  None

如果您的熊猫版本较旧，则可能需要将zip_longest包装在列表构造函数中.在较旧的Python上，您可能需要调用izip_longest而不是zip_longest.

If you have an older version of pandas you may need to wrap zip_longest in a list constructor. On older Python you may need to call izip_longest instead of zip_longest.

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