NumericColumn

NumericColumn(arg)

Methods

Name	Description
approx_quantile	Compute one or more approximate quantiles of a column.
bucket	Compute a discrete binning of a numeric array.
corr	Return the correlation of two numeric columns.
cov	Return the covariance of two numeric columns.
cummean	Return the cumulative mean of the input.
cumsum	Return the cumulative sum of the input.
histogram	Compute a histogram with fixed width bins.
mean	Return the mean of a numeric column.
std	Return the standard deviation of a numeric column.
sum	Return the sum of a numeric column.
var	Return the variance of a numeric column.

approx_quantile

approx_quantile(quantile, where=None)

Compute one or more approximate quantiles of a column.

The result may or may not be exact

Whether the result is an approximation depends on the backend.

Parameters

Name	Type	Description	Default
quantile	float \| ir.NumericValue \| Sequence[ir.NumericValue \| float]	`0 <= quantile <= 1`, or an array of such values indicating the quantile or quantiles to compute	required
where	ir.BooleanValue \| None	Boolean filter for input values	`None`

Returns

Name	Type	Description
	Scalar	Quantile of the input

Examples

>>> import ibis
>>> ibis.options.interactive = True
>>> t = ibis.examples.penguins.fetch()

Compute the approximate 0.50 quantile of bill_depth_mm.

>>> t.bill_depth_mm.approx_quantile(0.50)

┌────────┐
│ 17.318 │
└────────┘

Compute multiple approximate quantiles in one call - in this case the result is an array.

>>> t.bill_depth_mm.approx_quantile([0.25, 0.75])

┌────────────────────────┐
│ [15.565625, 18.671875] │
└────────────────────────┘

bucket

bucket(
    buckets,
    closed='left',
    close_extreme=True,
    include_under=False,
    include_over=False,
)

Compute a discrete binning of a numeric array.

Parameters

Name	Type	Description	Default
buckets	Sequence[int]	List of buckets	required
closed	Literal['left', 'right']	Which side of each interval is closed. For example: `python buckets = [0, 100, 200] closed = "left" # 100 falls in 2nd bucket closed = "right" # 100 falls in 1st bucket`	`'left'`
close_extreme	bool	Whether the extreme values fall in the last bucket	`True`
include_over	bool	Include values greater than the last bucket in the last bucket	`False`
include_under	bool	Include values less than the first bucket in the first bucket	`False`

Returns

Name	Type	Description
	IntegerColumn	A categorical column expression

corr

corr(right, where=None, how='sample')

Return the correlation of two numeric columns.

Parameters

Name	Type	Description	Default
right	NumericColumn	Numeric column	required
where	ir.BooleanValue \| None	Filter	`None`
how	Literal['sample', 'pop']	Population or sample correlation	`'sample'`

Returns

Name	Type	Description
	NumericScalar	The correlation of `left` and `right`

cov

cov(right, where=None, how='sample')

Return the covariance of two numeric columns.

Parameters

Name	Type	Description	Default
right	NumericColumn	Numeric column	required
where	ir.BooleanValue \| None	Filter	`None`
how	Literal['sample', 'pop']	Population or sample covariance	`'sample'`

Returns

Name	Type	Description
	NumericScalar	The covariance of `self` and `right`

cummean

cummean(where=None, group_by=None, order_by=None)

Return the cumulative mean of the input.

cumsum

cumsum(where=None, group_by=None, order_by=None)

Return the cumulative sum of the input.

histogram

histogram(nbins=None, binwidth=None, base=None, eps=1e-13)

Compute a histogram with fixed width bins.

Parameters

Name	Type	Description	Default
nbins	int \| None	If supplied, will be used to compute the binwidth	`None`
binwidth	float \| None	If not supplied, computed from the data (actual max and min values)	`None`
base	float \| None	The value of the first histogram bin. Defaults to the minimum value of `column`.	`None`
eps	float	Allowed floating point epsilon for histogram base	`1e-13`

Returns

Name	Type	Description
	Column	Bucketed column

mean

mean(where=None)

Return the mean of a numeric column.

Parameters

Name	Type	Description	Default
where	ir.BooleanValue \| None	Filter	`None`

Returns

Name	Type	Description
	NumericScalar	The mean of the input expression

std

std(where=None, how='sample')

Return the standard deviation of a numeric column.

Parameters

Name	Type	Description	Default
where	ir.BooleanValue \| None	Filter	`None`
how	Literal['sample', 'pop']	Sample or population standard deviation	`'sample'`

Returns

Name	Type	Description
	NumericScalar	Standard deviation of `arg`

sum

sum(where=None)

Return the sum of a numeric column.

Parameters

Name	Type	Description	Default
where	ir.BooleanValue \| None	Filter	`None`

Returns

Name	Type	Description
	NumericScalar	The sum of the input expression

var

var(where=None, how='sample')

Return the variance of a numeric column.

Parameters

Name	Type	Description	Default
where	ir.BooleanValue \| None	Filter	`None`
how	Literal['sample', 'pop']	Sample or population variance	`'sample'`

Returns

Name	Type	Description
	NumericScalar	Standard deviation of `arg`