:py:mod:`mathdistops.pnorm`
===========================

.. py:module:: mathdistops.pnorm


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   mathdistops.pnorm.pnorm



.. py:function:: pnorm(q, mean=0, std_dev=1, graph=True)

   Calculates Cumulative Probability of the normal distribution at this quantile and plots corresponding PDF and CDF.

   :param q: The quantile at which to evaluate the CDF.
   :type q: float
   :param mean: The mean (average) of the normal distribution. Default is 0.
   :type mean: float
   :param std_dev: The standard deviation of the normal distribution. Default is 1.
   :type std_dev: float
   :param graph: Whether to plot the PDF and CDF graph. Default is True.
   :type graph: bool

   :returns: **result** --

             If `graph` is True (default), returns a tuple consisting a pandas DataFrame and a
                 layered altair Chart consisting of two graphs, CDF and PDF.
             If `graph` is False, returns a pandas DataFrame.
   :rtype: pandas.DataFrame or tuple

   :raises ValueError:: If 'std_dev' is zero or negative, as the standard deviation must be a positive number.
   :raises TypeError:: If any of the input parameters ('q', 'mean', 'std_dev') are not numerical.

   .. rubric:: Example

   >>> pnorm(1, mean=0, std_dev=1, graph=False)
       Z-score    Cumulative probability
   0   1.0        0.8413447460685429