glucopy.Gframe.pcv#

Gframe.pcv(per_day: bool = False, ddof: int = 1)[source]#

Calculates the Percentage Coefficient of Variation (%CV) of the CGM values.

Parameters:

per_day (bool, default False) – If True, returns a pandas.Series with the percentage coefficient of variation for each day. If False, returns the percentage coefficient of variation for the entire dataset.
ddof (int, default 1) – Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. By default ddof is 1.

Returns:

pcv – Percentage coefficient of variation of the CGM values.

Return type:

float | pandas.Series

Examples

Calculating the percentage coefficient of variation for the entire dataset:

In [1]: import glucopy as gp

In [2]: gf = gp.data('prueba_1')

In [3]: gf.pcv()
Out[3]: 44.86303974875396

Calculating the percentage coefficient of variation for each day:

In [4]: gf.pcv(per_day=True)
Out[4]: 
Day
2020-11-27     8.765523
2020-11-28    31.600728
2020-11-29    42.977226
2020-11-30    25.808792
2020-12-01    30.317189
                ...    
2021-03-14    28.166254
2021-03-15    60.105356
2021-03-16    27.266636
2021-03-17    32.516196
2021-03-18    29.418785
Name: % Coefficient of Variation, Length: 112, dtype: float64