Other

Other modules

core

Main setup utilities.

statwrap.core.use_all(line)

Load the sheets and then fpp modules.

Parameters:

line (str) – Unused parameter retained for compatibility with IPython line magic.

Return type:

None

Examples

Using this function in IPython:

%use_all
statwrap.core.use_fpp(line)

Load the fpp module.

This imports functions that adhere to the conventions found in “Statistics” by Freedman, Pisani, and Purves.

Parameters:

line (str) – Unused parameter retained for compatibility with IPython line magic.

Return type:

None

Examples

Using this function in IPython:

%use_fpp
statwrap.core.use_sheets(line)

Load the sheets module.

This imports functions that adhere to the conventions specific to Google Sheets.

Parameters:

line (str) – Unused parameter retained for compatibility with IPython line magic.

Return type:

None

Examples

Using this function in IPython:

%use_sheets

utils

These are utilities agnostic to specific conventions.

class statwrap.utils.Formula(func)

This class is used to modify the display behavior of functions that have a mathematical formula.

class statwrap.utils.Hyperplane(*coefficients)

Represents a hyperplane in a multidimensional space.

The hyperplane is represented by the equation form:

\[y = c_0 + c_1 x_1 + c_2 x_2 + \ldots + c_n x_n\]

where c_i are the coefficients and x_i are the independent variables.

Parameters:

*coefficients (float) – The coefficients defining the hyperplane. c_0 is the constant term, and c_1, c_2, …, c_n are the coefficients of the variables x_1, x_2, …, x_n.

coefficients

An array holding the coefficients of the hyperplane.

Type:

ndarray

Examples

>>> plane = Hyperplane(1, 1, 1)
>>> plane(0, 1)
2
class statwrap.utils.RegressionLine(y, x, results)

RegressionLine class extends Hyperplane to model a univariate regression line with given coefficients, input values (x), and target values (y).

y

Target values.

Type:

array-like

x

Input values.

Type:

array-like

coefficients

Coefficients for the hyperplane.

Type:

tuple

residuals

Residuals of the regression.

Type:

array-like

predictions

Predicted values based on input x.

Type:

array-like

rms_error

Root Mean Square Error of the regression.

Type:

float

partial_regression_plot(show=True)

Shows a partial regression plot for each predictor variable.

plot(ax=None, show=True, scatter=True, **kwargs)

Make a plot with regression line. Only works for simple linear regression.

property predictions

Returns the predicted values based on input x.

residual_plot(**kwargs)

Shows a scatter plot of x vs the residuals.

property residuals

Returns the residuals of the regression.

property results

Returns the StatsModels results object.

property rms_error

Returns the Root Mean Square Error of the regression.

scatter_plot(**kwargs)

Shows a scatter plot for the data.

property x

Returns the input values.

property y

Returns the target values.

statwrap.utils.args_to_array(args)

When args is a tuple of scalars, this returns them in one array. When args’ first element is iterable, this returns the first element.

Find the first external link in a string formatted as LinkText <URL>.

Parameters: s (str): The string to search in.

Returns: (str, str): The first external link text and URL found, or (None, None) if no link is found.

statwrap.utils.formula(func)

Decorator to modify the display behavior of functions with a mathematical formula. The function should have its formula inside a math block in its docstring.

Decorator to modify the display behavior of functions with a hyperlink. The function should have its hyperlink inside its docstring.

statwrap.utils.modify_std(original_method)

Modifies a standard deviation method to adjust the ‘ddof’ parameter.

Parameters:

original_method (callable) – The original method for standard deviation or variance that accepts a ‘ddof’ parameter.

Returns:

A tuple containing two modified methods: - pop_std for population standard deviation (ddof=0) - sample_std for sample standard deviation (ddof=1).

Return type:

tuple of callables

Notes

If the ‘ddof’ parameter is already provided when calling the returned methods, it will not be overwritten.