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)
```
Syntax template for unary row-based functions:
```
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.
Syntax template for binary row-based functions:
```
rowFunc(X, Y)
```
Parameters:

X and Y are matrices/numeric vectors of the same size.

.

List of Functions

rowFunc(args…)
rowAnd, rowOr, rowXor, rowMax, rowMin, rowCount, rowSize, rowSum, rowSum2, rowAvg, rowProd, rowStd, rowStdp, rowVar, rowVarp
rowFunc(X, Y)
rowAt, rowBeta, rowCorr, rowCovar, rowWavg, rowWsum
Other Row-Based Functions:
(1) args is a matrix:
rowRank, rowDenseRank
(2) args is a tuple, matrix, or table
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)
// output
[23, 28, 33]

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)
// output
[8, 10, 9, 14, 6, 14]