Summary Statistics

summarize() computes the basic summary statistics of a set of numbers:

from tinytab import summarize

result = summarize([3.5, 2.25, 4.0, 1.75])
result

SummaryResult(n=4, mean=2.875, sd=1.051, min=1.75, max=4)

The result object

summarize() returns a SummaryResult, with one attribute per statistic:

result.mean, result.sd

(2.875, 1.050793351076541)

Attribute	Meaning
`n`	the number of values summarized
`mean`	the arithmetic mean
`sd`	the sample standard deviation (dividing by `n - 1`)
`min`, `max`	the smallest and largest values

The printed form rounds to four significant figures, to keep it readable. The attributes hold the full values.

A result can’t be changed after it’s created. Assigning to an attribute is an error:

result.mean = 0

---------------------------------------------------------------------------
FrozenInstanceError                       Traceback (most recent call last)
Cell In[3], line 1
----> 1 result.mean = 0

File <string>:19, in __create_fn__.<locals>.__setattr__(self, name, value)
     17 'Could not get source, probably due dynamically evaluated source code.'

FrozenInstanceError: cannot assign to field 'mean'

Missing values

Missing values, written as None or NaN, are left out of the calculation. Since dropping data silently could hide a problem, summarize() issues a warning saying how many were dropped:

import math

summarize([3.5, None, 4.0, math.nan])

/var/folders/s8/bj_jsx3d7jqd2btw7bwm6yx80000gp/T/ipykernel_51131/577297194.py:3: UserWarning: Dropped 2 missing value(s).
  summarize([3.5, None, 4.0, math.nan])

SummaryResult(n=2, mean=3.75, sd=0.3536, min=3.5, max=4)

If there are no values left to summarize, summarize() raises an error:

summarize([None, None])

/var/folders/s8/bj_jsx3d7jqd2btw7bwm6yx80000gp/T/ipykernel_51131/1716788409.py:1: UserWarning: Dropped 2 missing value(s).
  summarize([None, None])

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[5], line 1
----> 1 summarize([None, None])

File ~/py_projects/example-python-package/tinytab/_stats.py:93, in summarize(values)
     90     warnings.warn(f"Dropped {n_dropped} missing value(s).", UserWarning, stacklevel=2)
     92 if not clean:
---> 93     raise ValueError("Cannot summarize `values`: there are no non-missing values.")
     95 n = len(clean)
     96 mean = sum(clean) / n

ValueError: Cannot summarize `values`: there are no non-missing values.

A single value

With only one value, there’s no spread to measure, so the standard deviation is 0:

summarize([23])

SummaryResult(n=1, mean=23, sd=0, min=23, max=23)