python - 将 spark DataFrame 列转换为 python 列表

Question

我处理具有两列 mvv 和 count 的数据框。

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

我想获得两个包含 mvv 值和计数值的列表。类似的东西

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

所以，我尝试了以下代码:第一行应该返回一个 python 行列表。我想查看第一个值:

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

但我收到第二行的错误消息:

AttributeError: getInt

Answer 1

看看，为什么你的这种方式行不通。首先，您试图从 Row 中获取整数。类型，你收集的输出是这样的:

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

如果你采取这样的方式:

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

您将获得 mvv 值。如果你想要数组的所有信息，你可以这样:

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

但是，如果您对另一列尝试相同的操作，您会得到:

>>> 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'

这是因为 count 是一个内置方法。该列与 count 同名。解决方法是将 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()]

但不需要此解决方法，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()]

它最终会奏效!