从字符串列创建新列

Question

我有一个带有字符串列的 DataFrame

val df= Seq(("0003C32C-FC1D-482F-B543-3CBD7F0A0E36 0,8,1,799,300:3  0,6,1,330,300:1  2,6,1,15861:1 0,7,1,734,300:1 0,6,0,95,300:1 2,7,1,15861:1 0,8,0,134,300:3")).toDF("col_str")

+--------------------+
|             col_str|
+--------------------+
|0003C32C-FC1D-482...|
+--------------------+

字符串列由由空格分隔的字符序列组成。如果一个字符序列以 0 开头，我想返回序列的第二个数字和最后一个数字。第二个数字可以是 0 到 8 之间的任何数字。

Array("8,3", "6,1", "7,1", "6,1", "7,1", "8,3")

然后我想将数组对转换为 9 列，其中第一个数字作为列，第二个数字作为值。如果缺少一个数字，它将得到一个值 0。 例如

val df= Seq(("0003C32C-FC1D-482F-B543-3CBD7F0A0E36 0,8,1,799,300:3  0,6,1,330,300:1  2,6,1,15861:1 0,7,1,734,300:1 0,6,0,95,300:1 2,7,1,15861:1 0,8,0,134,300:1")).).toDF("col_str", "col0", "col1", "col2", "col3", "col4", "col5", "col6", "col7", "col8")

+--------------------+----+----+----+----+----+----+----+----+----+
|             col_str|col0|col1|col2|col3|col4|col5|col6|col7|col8|
+--------------------+----+----+----+----+----+----+----+----+----+
|0003C32C-FC1D-482...|   0|   0|   0|   0|   0|   0|   1|   1|   3|
+--------------------+----+----+----+----+----+----+----+----+----+

我不在乎解决方案是使用 scala 还是 python。

Answer 1

您可以执行以下操作（为清楚起见，请注释）

//string defining
val str = """0003C32C-FC1D-482F-B543-3CBD7F0A0E36 0,8,1,799,300:3  0,6,1,330,300:1  2,6,1,15861:1 0,7,1,734,300:1 0,6,0,95,300:1 2,7,1,15861:1 0,8,0,134,300:3"""
//string splitting with space
val splittedStr = str.split(" ")
//parsing the splitted string to get the desired format with the second element as key and the last element as value of the elements starting with 0
val parsedStr = List(("col_str"->splittedStr.head)) ++ splittedStr.tail.filter(_.startsWith("0")).map(value => {val splittedValue = value.split("[,:]"); ("col"+splittedValue(1)->splittedValue.last)}) toMap
//expected header names
val expectedHeader = Seq("col_str", "col0", "col1", "col2", "col3", "col4", "col5", "col6", "col7", "col8")
//populating 0 for the missing header names in the parsed string in above step
val missedHeaderWithValue = expectedHeader.diff(parsedStr.keys.toSeq).map((_->"0")).toMap
//combining both the maps
val expectedKeyValues = parsedStr ++ missedHeaderWithValue
//converting to a dataframe
Seq(expectedDF(expectedKeyValues(expectedHeader(0)), expectedKeyValues(expectedHeader(1)), expectedKeyValues(expectedHeader(2)), expectedKeyValues(expectedHeader(3)), expectedKeyValues(expectedHeader(4)), expectedKeyValues(expectedHeader(5)), expectedKeyValues(expectedHeader(6)), expectedKeyValues(expectedHeader(7)), expectedKeyValues(expectedHeader(8)), expectedKeyValues(expectedHeader(9))))
  .toDF()
  .show(false)

这应该给你

+------------------------------------+----+----+----+----+----+----+----+----+----+
|col_str                             |col0|col1|col2|col3|col4|col5|col6|col7|col8|
+------------------------------------+----+----+----+----+----+----+----+----+----+
|0003C32C-FC1D-482F-B543-3CBD7F0A0E36|0   |0   |0   |0   |0   |0   |1   |1   |3   |
+------------------------------------+----+----+----+----+----+----+----+----+----+

当然你需要expectedDFcase class在超出范围的地方定义

case class expectedDF(col_str: String, col0: String, col1: String, col2: String, col3: String, col4: String, col5: String, col6: String, col7: String, col8: String)