flatten

问题 I'm trying to remove the innermost nesting in a list of lists of single element length lists. Do you know a relatively easy way (converting to NumPy arrays is fine) to get from: [[[1], [2], [3], [4], [5]], [[6], [7], [8]], [[11], [12]]] to this?: [[1, 2, 3, 4, 5], [6, 7, 8], [11, 12]] Also, the real lists I'm trying to do this for contain datetime objects rather than ints in the example. And the initial collection of lists will be of varying lengths. Alternatively, it would be fine if there

问题 I'm trying to generify the transformation of a hierarchical array into a flat array. I have this kind of object which has children of the same type, which has children of the same type etc.. [{ id: "123", children: [ { id: "603", children: [ { id: "684", children: [ ... ] }, { id: "456", children: [] } ] } ] }] I found a way to flatten it and I have the information of the number of nested levels. One level deep (works): let result = myArray.flat() .concat(myArray.flatMap(comm => comm.children

问题 I have a nested structure read from YAML which is composed of nested lists and/or nested dicts or a mix of both at various levels of nesting. It can be assumed that the structure doesn't contain any recursive objects. How do I extract from it the leaf values only? Also, I don't want any None value. The leaf values contain strings which is all I care for. It's okay for recursion to be used, considering that the maximum depth of the structure is not large enough to exceed stack recursion limits

问题 I was trying to flatten the very nested JSON, and create spark dataframe and the ultimate goal is to push the given dataframe to phoenix. I am successfully able to flatten the JSON using code. def recurs(df: DataFrame): DataFrame = { if(df.schema.fields.find(_.dataType match { case ArrayType(StructType(_),_) | StructType(_) => true case _ => false }).isEmpty) df else { val columns = df.schema.fields.map(f => f.dataType match { case _: ArrayType => explode(col(f.name)).as(f.name) case s:

问题 I have a Spark job, which has a DataFrame with the following value : { "id": "abchchd", "test_id": "ndsbsb", "props": { "type": { "isMale": true, "id": "dd", "mcc": 1234, "name": "Adam" } } } { "id": "abc", "test_id": "asf", "props": { "type2": { "isMale": true, "id": "dd", "mcc": 12134, "name": "Perth" } } } and I want to flatten it out elegantly (as no of keys is unknown and type etc) in such a way that props remains as a struct but everything inside it is flattened off (irrespective of the

问题 I've been having a little trouble trying to flatten arrays in a specific way. Here is a print_r view of the array I want to flatten: Array ( [1] => Array ( [8] => 1 [9] => 2 [10] => Array ( [15] => Array ( [22] => 1 ) [21] => 2 ) [11] => Array ( [16] => Array ( [23] => 1 ) ) ) [2] => Array ( [12] => 1 ) [3] => Array ( [13] => 1 ) [4] => Array ( [14] => 1 ) [5] => 5 [6] => 6 [7] => 7 ) What I'm attempting to create is an array which keeps the above indexes, but the value is equal to it's

问题 I'm struggling to create the right logic to flatten an array. I essentially want to duplicate parent rows for each child item in a nested array. The number of nested arrays could vary. I've been creating Java lists bc I find them easy to work with, but open to any solution. The nature of this problem is I'm starting with some nested JSON that I want to convert into a flat csv to load into a database table. Thanks for the help. Example: [1,2,[A,B,[Cat,Dog]],3] I've created the above as a List.

问题 Given a list of arbitrairly deep nested lists of arbitrary size, I would like an flat, depth-first iterator over all elements in the tree, but with path indicies as well such that: for x, y in flatten(L), x == L[y[0]][y[1]]...[y[-1]]. That is L = [[[1, 2, 3], [4, 5]], [6], [7,[8,9]], 10] flatten(L) should yield: (1, (0, 0, 0)), (2, (0, 0, 1)), (3, (0, 0, 2)), (4, (0, 1, 0)), (5, (0, 1, 1)), (6, (1, 0)), (7, (2, 0)), (8, (2, 1, 0)), (9, (2, 1, 1)), (10, (3,)) I made a recursive implementation

问题 Given a list of arbitrairly deep nested lists of arbitrary size, I would like an flat, depth-first iterator over all elements in the tree, but with path indicies as well such that: for x, y in flatten(L), x == L[y[0]][y[1]]...[y[-1]]. That is L = [[[1, 2, 3], [4, 5]], [6], [7,[8,9]], 10] flatten(L) should yield: (1, (0, 0, 0)), (2, (0, 0, 1)), (3, (0, 0, 2)), (4, (0, 1, 0)), (5, (0, 1, 1)), (6, (1, 0)), (7, (2, 0)), (8, (2, 1, 0)), (9, (2, 1, 1)), (10, (3,)) I made a recursive implementation

问题 I have an array of array, something like that: array([[array([33120, 28985, 9327, 45918, 30035, 17794, 40141, 1819, 43668], dtype=int64)], [array([33754, 24838, 17704, 21903, 17668, 46667, 17461, 32665], dtype=int64)], [array([46842, 26434, 39758, 27761, 10054, 21351, 22598, 34862, 40285, 17616, 25146, 32645, 41276], dtype=int64)], ..., [array([24534, 8230, 14267, 9352, 3543, 29397, 900, 32398, 34262, 37646, 11930, 37173], dtype=int64)], [array([25157], dtype=int64)], [array([ 8859, 20850,