mathdistops.pnorm

Module Contents

Functions

pnorm(q[, mean, std_dev, graph])

Calculates Cumulative Probability of the normal distribution at this quantile and plots corresponding PDF and CDF.
mathdistops.pnorm.pnorm(q, mean=0, std_dev=1, graph=True)[source]

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

Parameters:

  • q (float) – The quantile at which to evaluate the CDF.

  • mean (float) – The mean (average) of the normal distribution. Default is 0.

  • std_dev (float) – The standard deviation of the normal distribution. Default is 1.

  • graph (bool) – Whether to plot the PDF and CDF graph. Default is True.

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.

Return type:

pandas.DataFrame or tuple

Raises:

  • ValueError: – If ‘std_dev’ is zero or negative, as the standard deviation must be a positive number.

  • TypeError: – If any of the input parameters (‘q’, ‘mean’, ‘std_dev’) are not numerical.

Example

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