将spark DataFrame列转换为python列表

Question

+---+-----+
|mvv|count|
+---+-----+
| 1 |  5  |
| 2 |  9  |
| 3 |  3  |
| 4 |  1  |

mvv = [1,2,3,4]
count = [5,9,3,1]

mvv_list = mvv_count_df.select('mvv').collect()
firstvalue = mvv_list[0].getInt(0)

但我得到第二行的错误消息：

AttributeError：getInt

Answer 1

看，为什么你这样做是不起作用的。首先，您试图从行类型获取integer，collect的输出如下所示：

>>> mvv_list = mvv_count_df.select('mvv').collect()
>>> mvv_list[0]
Out: Row(mvv=1)

如果你拿这样的东西：

>>> firstvalue = mvv_list[0].mvv
Out: 1

您将获得MVV值。如果您想要数组的所有信息，您可以使用如下所示：

>>> mvv_array = [int(row.mvv) for row in mvv_list.collect()]
>>> mvv_array
Out: [1,2,3,4]

但是，如果您对其他列进行相同的尝试，您将得到：

>>> mvv_count = [int(row.count) for row in mvv_list.collect()]
Out: TypeError: int() argument must be a string or a number, not 'builtin_function_or_method'

发生这种情况是因为count是一个内置方法。并且列的名称与count相同。解决办法是将count的列名更改为_count:

>>> mvv_list = mvv_list.selectExpr("mvv as mvv", "count as _count")
>>> mvv_count = [int(row._count) for row in mvv_list.collect()]

但是不需要这种变通方法，因为您可以使用字典语法访问该列：

>>> mvv_array = [int(row['mvv']) for row in mvv_list.collect()]
>>> mvv_count = [int(row['count']) for row in mvv_list.collect()]