Stairs methods

Constructor & basic methods

Stairs([value, use_dates, tz]) An instance of a Stairs class is used to represent a step function.
Stairs.copy([deep]) Returns a deep copy of this Stairs instance
Stairs.plot([ax]) Makes a step plot representing the finite intervals belonging to the Stairs instance.
Stairs.sample(x[, how, aggfunc, window, …]) Evaluates the value of the step function at one, or more, points.
Stairs.layer([start, end, value]) Changes the value of the step function.
Stairs.step_changes() Returns a dictionary of key, value pairs of indicating where step changes occur in the step function, and the change in value
Stairs.to_dataframe() Returns a pandas.DataFrame with columns ‘start’, ‘end’ and ‘value’

Arithmetic operators

Stairs.negate() An operator which produces a new Stairs instance representing the multiplication of the step function by -1.
Stairs.add(other) A binary operator facilitating the addition of step functions.
Stairs.subtract(other) A binary operator facilitating the subtraction of step functions.
Stairs.multiply(other) A binary operator facilitating the multiplication of step functions.
Stairs.divide(other) A binary operator facilitating the division of step functions.

Relational operators

Stairs.lt(other) Returns a boolean-valued step function indicating where self is strictly less than other.
Stairs.gt(other) Returns a boolean-valued step function indicating where self is strictly greater than other.
Stairs.le(other) Returns a boolean-valued step function indicating where self is less than, or equal to, other.
Stairs.ge(other) Returns a boolean-valued step function indicating where self is greater than, or equal to, other.
Stairs.eq(other) Returns a boolean-valued step function indicating where self is equal to other.
Stairs.ne(other) Returns a boolean-valued step function indicating where self is not equal to other.
Stairs.identical(other) Returns True if self and other represent the same step functions.

Logical operators

Stairs.make_boolean() Returns a boolean-valued step function indicating where self is non-zero.
Stairs.invert() Returns a boolean-valued step function indicating where self is zero-valued.
Stairs.logical_and(other) Returns a boolean-valued step function indicating where self and other are non-zero.
Stairs.logical_or(other) Returns a boolean-valued step function indicating where self or other are non-zero.

Statistical operators

Stairs.cov(other[, lower, upper, lag, clip]) Calculates either covariance, autocovariance or cross-covariance.
Stairs.corr(other[, lower, upper, lag, clip]) Calculates either correlation, autocorrelation or cross-correlation.

Summary statistics

Stairs.number_of_steps() Calculates the number of step changes
Stairs.get_integral_and_mean([lower, upper]) Calculates the integral, and the mean of the step function.
Stairs.integrate([lower, upper]) Calculates the integral of the step function.
Stairs.describe([lower, upper, percentiles]) Generate descriptive statistics.
Stairs.min([lower, upper, lower_how, upper_how]) Calculates the minimum value of the step function
Stairs.max([lower, upper, lower_how, upper_how]) Calculates the maximum value of the step function
Stairs.var([lower, upper]) Calculates the variance of the step function.
Stairs.std([lower, upper]) Calculates the standard deviation of the step function.
Stairs.mean([lower, upper]) Calculates the mean of the step function.
Stairs.median([lower, upper]) Calculates the median of the step function.
Stairs.percentile(x[, lower, upper]) Calculates the x-th percentile of the step function.
Stairs.percentile_stairs([lower, upper]) Calculates a percentile function (and returns a corresponding Stairs instance)
Stairs.ecdf_stairs([lower, upper]) Calculates an empirical cumulative distribution function for the corresponding step function values (and returns the result as a Stairs instance)
Stairs.hist([lower, upper, bin_edges, closed]) Calculates a histogram for the corresponding step function values

Miscellaneous functions

Stairs.clip([lower, upper]) Returns a copy of self which is zero-valued everywhere outside of [lower, upper)
Stairs.shift(delta) Returns a stairs instance corresponding to a horizontal translation by delta
Stairs.diff(delta) Returns a stairs instance corresponding to the difference between the step function corresponding to self and the same step-function translated by delta.
Stairs.rolling_mean([window, lower, upper]) Returns coordinates defining rolling mean
Stairs.resample(x[, how, aggfunc, window, …]) Evaluates the value of the step function at one, or more, points and creates a new Stairs instance whose step changes occur at a subset of these points.
Stairs.clip([lower, upper]) Returns a copy of self which is zero-valued everywhere outside of [lower, upper)