如何将Python字典对象转换为numpy数组 [英] How to convert Python dictionary object to numpy array

问题描述

我有python dict对象，其键为datetime.date对象，值为元组对象:

I have python dict object with key as datetime.date object and values as tuple objects:

>>> data_dict
{datetime.date(2006, 1, 1): (5, 3),
 datetime.date(2006, 1, 2): (8, 8),
 datetime.date(2006, 1, 3): (8, 5),
 datetime.date(2006, 1, 4): (3, 3),
 datetime.date(2006, 1, 5): (3, 3),
 datetime.date(2006, 1, 6): (4, 3),
...

，我想将其转换为以下格式的numpy数组对象:

and I want to convert it to numpy array object in this format:

dtype([('date', '|O4'), ('high', '<i1'), ('low', '<i1')])

这样我就可以将其存储在磁盘上，以后再使用它，并在numpy中学习matplotlib ...

so that I could store it on disk and later work with it, and learn, in numpy, matplotlib...

事实上，我认为在查看以下matplotlib示例后，便会使用这种格式: http ://matplotlib.sourceforge.net/users/recipes.html ，但找不到解决方法.

As a matter of fact, I thought to use this format after looking at this matplotlib examples: http://matplotlib.sourceforge.net/users/recipes.html but can't find my way out how to get there.

推荐答案

以下将完成此操作:

arr = np.array([(k,)+v for k,v in data_dict.iteritems()], \
         dtype=[('date', '|O4'), ('high', '<f8'), ('low', '<f8')])

如果您随后希望将arr用作 recarray ，您可以使用:

If you then wish to use arr as a recarray, you could use:

arr = arr.view(np.recarray)

这将使您能够按名称引用字段，例如arr.date.

This will enable you to reference fields by name, e.g. arr.date.

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