R help - Aug 2021 - Calculate daily means from 5-minute interval data

On Sun, 29 Aug 2021, Jeff Newmiller wrote:
> The general idea is to create a "grouping" column with repeated
values for
> each day, and then to use aggregate to compute your combined results. The
> dplyr package's group_by/summarise functions can also do this, and
there
> are also proponents of the data.table package which is high performance
> but tends to depend on altering data in-place unlike most other R data
> handling functions.
>
> Also pay attention to missing data... if you have any then you will need
> to consider whether you want the strictness of na.rm=FALSE or
> permissiveness of na.rm=TRUE for your aggregation functions.
Jeff,

Thank you. Yes, there are missing data as sometimes the equipment fails, or
there's some other reason why some samples are missing.

Grouping on each day is just what I need. I'll re-learn dplyr and take a
look at data.table.

Regards,

Rich

Hello,

I forgot in my previous answer, sorry for the duplicated mails.

The function in my previous mail has a na.rm argument, defaulting to 
FALSE, pass na.rm = TRUE to remove the NA's.


agg <- aggregate(cfs ~ date, df1, fun, na.rm = TRUE)



Or simply change the default. I prefer to set na.rm = FALSE because 
that's what R's functions do. And I will only be used to one default, 
with base R functions or my own code.


Hope this helps,

Rui Barradas

?s 17:52 de 29/08/21, Rich Shepard escreveu:
> On Sun, 29 Aug 2021, Jeff Newmiller wrote:
> 
>> The general idea is to create a "grouping" column with
repeated values
>> for
>> each day, and then to use aggregate to compute your combined results.
The
>> dplyr package's group_by/summarise functions can also do this, and
there
>> are also proponents of the data.table package which is high performance
>> but tends to depend on altering data in-place unlike most other R data
>> handling functions.
>>
>> Also pay attention to missing data... if you have any then you will
need
>> to consider whether you want the strictness of na.rm=FALSE or
>> permissiveness of na.rm=TRUE for your aggregation functions.
> 
> Jeff,
> 
> Thank you. Yes, there are missing data as sometimes the equipment fails, or
> there's some other reason why some samples are missing.
> 
> Grouping on each day is just what I need. I'll re-learn dplyr and take
a
> look at data.table.
> 
> Regards,
> 
> Rich
> 
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