C(data[, contrast, levels]) |
Marks some data as being categorical, and specifies how to interpret it. |
I(x) |
The identity function. |
Q(name) |
A way to ‘quote’ variable names, especially ones that do not otherwise meet Python’s variable name rules. |
bs(x[, df, knots, degree, ...]) |
Generates a B-spline basis for x, allowing non-linear fits. |
cc(x[, df, knots, lower_bound, upper_bound, ...]) |
Generates a cyclic cubic spline basis for x (with the option of absorbing centering or more general parameters constraints), allowing non-linear fits. |
center(x) |
A stateful transform that centers input data, i.e., subtracts the mean. |
cr(x[, df, knots, lower_bound, upper_bound, ...]) |
Generates a natural cubic spline basis for x (with the option of absorbing centering or more general parameters constraints), allowing non-linear fits. |
scale(*args, **kwargs) |
standardize(x, center=True, rescale=True, ddof=0) |
standardize(x[, center, rescale, ddof]) |
A stateful transform that standardizes input data, i.e. |
te(s1, .., sn[, constraints]) |
Generates smooth of several covariates as a tensor product of the bases of marginal univariate smooths s1, .., sn. |
test_I() |
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test_Q() |
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