numpy.genfromtxt和numpy.loadtxt之间的区别，以及Unpack [英] Difference Between numpy.genfromtxt and numpy.loadtxt, and Unpack

问题描述

我对Python非常陌生 - 实际上，对于编程来说一般都是新手，尽管我恐怕我不能永远使用这个借口 - 并且很想知道标题中提到的两个函数之间的区别这个线程。从包含文档的网站上，它说：当没有数据丢失时，numpy.loadtxt [是] [等同]功能。究竟是什么意思？这是否意味着，例如，如果我有一个csv文件，其中包含数据的两列之间有一个空白列，我不应该numpy.loadtxt。

I am rather new to python--actually, new to programming in general, though I am afraid I can't use that excuse forever--, and am curious to know the difference between the two functions alluded to in the title of this thread. From the website containing the documentation, it says, "numpy.loadtxt [is] [an] equivalent function when no data is missing." What exactly is meant by this? Does this mean, for instance, if I have a csv file that has a blank column between two columns containing data, I should not numpy.loadtxt.

另外，什么这意味着，

Also, what does this mean,

"unpack : bool, optional
If True, the returned array is transposed, so that arguments may be unpacked using x, y, z = loadtxt(...)"

我不太确定至于这是什么意思。

I am not quite certain as to what this means.

我很感谢您的帮助，谢谢！

I'd appreciate your help, thank you!

推荐答案

你是对的。使用 np.genfromtxt 给出一些选项，如参数 missing_values ， filling_values 可以帮助你处理一个不完整的 csv 。例如：

You are correct. Using np.genfromtxt gives you some options like the parameters missing_values, filling_values that can help you dealing with an incomplete csv. Example:

1,2,,,5
6,,8,,
11,,,,

可以阅读：

Could be read with:

filling_values = (111, 222, 333, 444, 555) # one for each column
np.genfromtxt(filename, delimiter=',', filling_values=filling_values) 
#array([[   1.,    2.,  333.,  444.,    5.],
#       [   6.,  222.,    8.,  444.,  555.],
#       [  11.,  222.,  333.,  444.,  555.]])

参数 unpack 当你想将文本文件的每一列放入一个不同的变量时非常有用。例如，您的文本文件中包含 x，y，z 列，则：

The parameter unpack is useful when you want to put each column of the text file in a different variable. Example, you have the text file with columns x, y, z, then:

x, y, z = np.loadtxt(filename, unpack=True)

这与

x, y, z = np.loadtxt(filename).T

默认情况下，遍历二维数组意味着迭代行，这就是为什么您必须转置或使用 unpack = True 在这个例子中。

By default iterating over a 2-D array means iterating over the lines, that's why you have to transpose or use unpack=True in this example.

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