datatable.min()

datatable.

min

(

cols

)

sourcetests

Calculate the minimum value for each column from cols. It is recommended to use it as dt.min() to prevent conflict with the Python built-in min() function.

Parameters

cols

FExpr

Input columns.

return

Expr

f-expression having one row and the same names, stypes and number of columns as in cols.

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, 1, 2, 2, 2, 3, 3, 3], 'B': [3, 2, 20, 1, 6, 2, 3, 22, 1]}) df

	A	B
	int32	int32
0	1	3
1	1	2
2	1	20
3	2	1
4	2	6
5	2	2
6	3	3
7	3	22
8	3	1

9 rows × 2 columns

Get the minimum from column B:

df[:, dt.min(f.B)]

	B
	int32
0	1

1 row × 1 column

Get the minimum of all columns:

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

	A	B
	int32	int32
0	1	1

1 row × 2 columns

Same as above, but using the slice notation:

df[:, dt.min(f[:])]

	A	B
	int32	int32
0	1	1

1 row × 2 columns

You can pass in a dictionary with new column names:

df[:, dt.min({"A_min": f.A, "B_min": f.B})]

	A_min	B_min
	int32	int32
0	1	1

1 row × 2 columns

In the presence of by(), it returns the row with the minimum value per group:

df[:, dt.min(f.B), by("A")]

	A	B
	int32	int32
0	1	2
1	2	1
2	3	1

3 rows × 2 columns