datatable.rowsd()

datatable.

rowsd

(

*cols

)

sourcetests

For each row, find the standard deviation among the columns from cols skipping missing values. If a row contains only the missing values, this function will produce a missing value too.

Parameters

cols

FExpr

Input columns.

return

FExpr

f-expression consisting of one column that has the same number of rows as in cols. The column stype is float32 when all the cols are float32, and float64 in all the other cases.

except

TypeError

The exception is raised when cols has non-numeric columns.

Examples

from datatable import dt, f, rowsd DT = dt.Frame({'name': ['A', 'B', 'C', 'D', 'E'], 'group': ['mn', 'mn', 'kl', 'kl', 'fh'], 'S1': [1, 4, 5, 6, 7], 'S2': [2, 3, 8, 5, 1], 'S3': [8, 5, 2, 5, 3]}

DT

	name	group	S1	S2	S3
	str32	str32	int32	int32	int32
0	A	mn	1	2	8
1	B	mn	4	3	5
2	C	kl	5	8	2
3	D	kl	6	5	5
4	E	fh	7	1	3

5 rows × 5 columns

Get the row standard deviation for all integer columns:

DT[:, rowsd(f[int])]

	C0
	float64
0	3.78594
1	1
2	3
3	0.57735
4	3.05505

5 rows × 1 column

Get the row standard deviation for some columns:

DT[:, rowsd(f[2, 3])]

	C0
	float64
0	0.707107
1	0.707107
2	2.12132
3	0.707107
4	4.24264

5 rows × 1 column

See Also

• rowmean() – calculate the mean value row-wise.