>
>
> >I was going to suggest the same thing: type casting can have
> >non-obvious effects, so explicit is better than implicit in this case.
>
> Aye. Did you mean to send this just to me and not the list?
>
nope -- I know i"m in the minority but i really wish lists had reply-to set
to the list.
On 13May2022 00:17, Steven D'Aprano wrote:
>Users of the statistics module, how often do you use it with
>heterogeneous data (mixed numeric types)?
Disclaimer: I am not yet a user of the statistics module.
>With mixed types, the functions usually try to coerce the values into a
>sensible common
On Fri, 13 May 2022 at 00:20, Steven D'Aprano wrote:
>
> If you are a user of statistics, how important to you is the ability to
> **mix** numeric types, in the same data set?
>
> Which combinations do you care about?
>
I'm only a very small-time user of it, but the only combination I use
is int
IMHO, mixing custom types in this context is usually not required, as long
as at least int-to-anything-else typecast is possible. Currently it's done
only when there is at least one non-int and when the result can't be
represented as int, that is:
>>> statistics.mean([1, 2, 3, 6])
3
>>> statistics
Hi Steve
Today's XKCD is on 'Selection Bias' and it is set in a statistics
conference: https://xkcd.com/2618/
According to its PEP the statistics module provides "common statistics
functions such as mean, median, variance and standard deviation".
You ask "if you are a user of statistics, how imp
