如何将 pandas 数据框行快速转换为ordereddict [英] How to turn pandas dataframe row into ordereddict fast

问题描述

寻找一种快速的方法来在不使用list的情况下将pandas数据框中的一行转换为有序dict.列表很好，但是具有大数据集将花费很长时间.我正在使用fiona GIS阅读器，并且行使用了给出数据类型的模式进行了排序.我使用熊猫来连接数据.在很多情况下，行的类型会有所不同，因此我想将字符串类型转换为numpy数组可能会解决问题.

Looking for a fast way to get a row in a pandas dataframe into a ordered dict with out using list. List are fine but with large data sets will take to long. I am using fiona GIS reader and the rows are ordereddicts with the schema giving the data type. I use pandas to join data. I many cases the rows will have different types so I was thinking turning into a numpy array with type string might do the trick.

推荐答案

不幸的是，您不能只进行申请(因为它适合于DataFrame):

Unfortunately you can't just do an apply (since it fits it back to a DataFrame):

In [1]: df = pd.DataFrame([[1, 2], [3, 4]], columns=['a', 'b'])

In [2]: df
Out[2]: 
   a  b
0  1  2
1  3  4

In [3]: from collections import OrderedDict

In [4]: df.apply(OrderedDict)
Out[4]: 
   a  b
0  1  2
1  3  4

但是您可以将列表理解与 iterrows :

But you can use a list comprehension with iterrows:

In [5]: [OrderedDict(row) for i, row in df.iterrows()]
Out[5]: [OrderedDict([('a', 1), ('b', 2)]), OrderedDict([('a', 3), ('b', 4)])]

如果可以使用生成器而不是列表，则无论使用哪种生成器，效率通常都会更高:

If it was possible to use a generator, rather than a list, to whatever you were working with this will usually be more efficient:

In [6]: (OrderedDict(row) for i, row in df.iterrows())
Out[6]: <generator object <genexpr> at 0x10466da50>

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