Row-Based Functions

For most DolphinDB functions that are applicable to matrices or tables, the calculation is usually conducted based on columns. To calculate on rows, you can use row-based functions.

Introduction

  • Higher-order function byRow :

$ byRow(func, X)
  • General templates for row-based functions are:

Template 1

$ rowFunc(args…)

Parameters

args can be a scalar/matrix, or one or more vectors/tuples/tables or their combination. The length of vector, the number of elements of a tuple, and the number of table columns must be the same.

Note: If args is a matrix, return a vector of the same length as the number of rows of the matrix. Please note that multiple matrices are not supported in row functions.

Template 2 (released with version 2.00.4)

$ rowFunc(X, Y)

Parameters

X and Y are matrices of the same size or vectors/array vectors with the same number of rows.

List of Functions

Other Row-Based Functions:

See also

args is a matrix:

rowRank, rowDenseRank.

args can be vectors, tuples, matrices or tables:

rowKurtosis, rowSkew

Calculation Rules

To calculate on different data forms, please see the following example.

$ vec = [1,2,3]
$ vec_tuple = [[3,4,5],[4,5,6]]
$ tb = table(7 8 9 as id, 8 9 10 as code)
$ print rowSum(vec, vec_tuple, tb)
[23, 28, 33]
../../_images/rowfunc_1.png

To calculation on a matrix:

$ m = matrix(4 2 1 3 5 8, 1 2 5 9 0 1, 3 6 3 2 1 5)
$ print rowSum(m)
[8, 10, 9, 14, 6, 14]