Pandas:一种使用namedtuple列表初始化数据帧的干净方法

问题描述

我是熊猫新手，所以也许我在问一个非常愚蠢的问题.通常，大熊猫中数据帧的初始化是按列的，在这里，我用列名的键和长度相同的类似列表的对象的值放入dict.

I'm new to pandas, therefore perhaps I'm asking a very stupid question. Normally initialization of data frame in pandas would be column-wise, where I put in dict with key of column names and values of list-like object with same length.

但是我很想在不动态连接行的情况下按行初始化.说我有一个namedtuple列表，是否有优化的操作可以直接给我一个熊猫数据框?

But I would love to initialize row-wise without dynamically concat-ing rows. Say I have a list of namedtuple, is there a optimized operation that will give me a pandas data frame directly from it?

非常感谢

推荐答案

您想要的功能是 from_records .

对于namedtuple实例，除了命名元组列表之外，还必须将namedtuple的_fields属性传递给from_records的columns参数:

For namedtuple instances you must pass the _fields property of the namedtuple to the columns parameter of from_records, in addition to a list of namedtuples:

df = pd.DataFrame.from_records(
   [namedtuple_instance1, namedtuple_instance2],
   columns=namedtuple_type._fields
)

如果您有字典，可以直接将其用作

If you have dictionaries, you can use it directly as

df = pd.DataFrame.from_records([dict(a=1, b=2), dict(a=2, b=3)])

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