将读入的多维list转为一维list的方法(python)

第一种：使用extend()

>>> lines = open("test.txt").readlines()
>>> lines
["1 ", "2 ", "3 ", "4,5 "]
>>> for line in lines:
...     ll.extend(line.strip().split(","))
...
>>> ll
["1", "2", "3", "4", "5"]

第二种：使用+

>>> ll = []
>>> lines = open("test.txt").readlines()
>>> lines
["1 ", "2 ", "3 ", "4,5 "]
>>> for line in lines:
...     ll = ll + line.strip().split(",")
...
>>> ll
["1", "2", "3", "4", "5"]

第三种：使用flat array数组的自带方法

>>> ll = []
>>> lines = open("test.txt").readlines()
>>> for line in lines:
...     ll.append(line.strip().split(","))
...
>>> ll = np.array(ll)
>>> np.hstack(ll.flat)
array(["1", "2", "3", "4", "5"],
      dtype="|S1")
>>> list(np.hstack(ll.flat))
["1", "2", "3", "4", "5"]

总结：

1. extend()与append()的区别

append()可以接受任何数据类型和格式的数据作为一个元素插入原list

extend() 则仅能将任何数据类型和格式的数据展开作为一组元素插入原list

eg.

>>> a = [1,"a"]
>>> a.extend(np.array([2,"b"]))
>>> a
[1, "a", "2", "b"]
>>> a.extend([3,["c"]])
>>> a
[1, "a", "2", "b", 3, ["c"]]

>>> a = [1,"a"]
>>> a.extend(np.array([2,"b"]))
>>> a
[1, "a", "2", "b"]
>>> a.extend([3,["c"]])
>>> a
[1, "a", "2", "b", 3, ["c"]]

>>> a = [1,"a"]
>>> a.append(np.array([2,"b"]))
>>> a
[1, "a", array(["2", "b"],
      dtype="|S21")]
>>> a.append([3,["c"]])
>>> a
[1, "a", array(["2", "b"],
      dtype="|S21"), [3, ["c"]]]

2. flatten()无法对dtype = object的array进行展开，dtype = object说明array中的元素是list，即其不是满矩阵结构

eg.

>>> a = np.array([[1,2],[3,4]])
>>> a.dtype
dtype("int64")
>>> a.flatten()
array([1, 2, 3, 4])
>>>
>>> a = np.array([[1,2],[3,4],[5]])
>>> a.flatten()
array([[1, 2], [3, 4], [5]], dtype=object)

3.readlines读取文件默认str，可以通过map转换数据类型

eg.

>>> ll = []
>>> lines = open("test.txt").readlines()
>>> lines
["1 ", "2 ", "3 ", "4,5 "]
>>> for line in lines:
...     ll.append(map(int,line.strip().split(",")))
...
>>> ll
[[1], [2], [3], [4, 5]]