datatable.sum()

datatable.

sum

(

cols

)

sourcetests

Calculate the sum of values for each column from cols. The sum of the missing values is calculated as zero.

Parameters

cols

FExpr

Input columns.

return

FExpr

f-expression having one row, and the same names and number of columns as in cols. The column types are int64 for void, boolean and integer columns, float32 for float32 columns and float64 for float64 columns.

except

TypeError

The exception is raised when one of the columns from cols has a non-numeric type.

Examples

from datatable import dt, f, by df = dt.Frame({'A': [1, 1, 2, 1, 2], 'B': [None, 2, 3, 4, 5], 'C': [1, 2, 1, 1, 2]}) df

	A	B	C
	int32	int32	int32
0	1	NA	1
1	1	2	2
2	2	3	1
3	1	4	1
4	2	5	2

5 rows × 3 columns

Get the sum of column A:

df[:, dt.sum(f.A)]

	A
	int64
0	7

1 row × 1 column

Get the sum of multiple columns:

df[:, [dt.sum(f.A), dt.sum(f.B)]]

	A	B
	int64	int64
0	7	14

1 row × 2 columns

Same as above, but more convenient:

df[:, dt.sum(f[:2])]

	A	B
	int64	int64
0	7	14

1 row × 2 columns

In the presence of by(), it returns the sum of the specified columns per group:

df[:, [dt.sum(f.A), dt.sum(f.B)], by(f.C)]

	C	A	B
	int32	int64	int64
0	1	4	7
1	2	3	7

2 rows × 3 columns

See Also

• .sum() – the corresponding Frame’s method for multi-column frames.

• .sum1() – the corresponding Frame’s method for single-column frames that returns a scalar value.

• count() – function to calculate a number of non-missing values.