datatable.cut()

datatable.

cut

(

cols

,

nbins=10

,

bins=None

,

right_closed=True

)

sourcetests

Added in version 0.11

For each column from cols bin its values into equal-width intervals, when nbins is specified, or into arbitrary-width intervals, when interval edges are provided as bins.

Parameters

cols

FExpr

Input data for equal-width interval binning.

nbins

int | List[int]

When a single number is specified, this number of bins will be used to bin each column from cols. When a list or a tuple is provided, each column will be binned by using its own number of bins. In the latter case, the list/tuple length must be equal to the number of columns in cols.

bins

List[Frame]

A list or a tuple of frames for binning the corresponding columns from cols. Each frame should have only one column that is populated with the edges of the binning intervals in strictly increasing order. Number of elements in bins must be equal to the number of columns in cols.

right_closed

bool

Each binning interval is half-open. This flag indicates whether the right edge of the interval is closed, or not.

return

FExpr

f-expression that converts input columns into the columns filled with the respective bin ids.

Examples

Bin one-column frame by specifying a number of bins:

from datatable import dt, f, cut DT = dt.Frame([1, 3, 5]) DT[:, cut(f[:], nbins = 5)]

	C0
	int32
0	0
1	2
2	4

3 rows × 1 column

Bin one-column frame by specifying edges of the binning intervals:

from datatable import dt, f, cut DT = dt.Frame([1, 3, 5]) BINS = [dt.Frame(range(5))] DT[:, cut(f[:], bins = BINS)] # Note, "5" goes out of bounds and is binned as "NA"

	C0
	int32
0	0
1	2
2	NA

3 rows × 1 column

Bin two-column frame by specifying a number of bins for each column separately:

from datatable import dt, f, cut DT = dt.Frame([[1, 3, 5], [5, 7, 9]]) DT[:, cut(f[:], nbins = [5, 10])]

	C0	C1
	int32	int32
0	0	0
1	2	4
2	4	9

3 rows × 2 columns

Bin two-column frame by specifying edges of the binning intervals:

from datatable import dt, f, cut DT = dt.Frame([[1, 3, 5], [0.1, -0.1, 1.5]]) BINS = [dt.Frame(range(10)), dt.Frame([-1.0, 0, 1.0, 2.0])] DT[:, cut(f[:], bins = BINS)]

	C0	C1
	int32	int32
0	0	1
1	2	0
2	4	2

3 rows × 2 columns

See also

qcut() – function for equal-population binning.