I need to compute some descriptive statistics, such as median, variance, and standard deviation of various dataframes. All dataframes, about 300, have the same amounts of variables, but the number of observations differs from one to the other, just as the values. Since I have not yet been able to generate this loop, I am first trying to run in a single dataframe, a loop that can generate the statistics, breaking the dataframe always into groups of seven observations.
The first dataframe I'm working on to generate the loop that will make the basic statistics is this:
# A tibble: 363 x 4
Day Location Flow Qty
<dttm> <chr> <dbl> <dbl>
1 2014-03-03 ABC_100 4948 1637.10
2 2014-03-04 ABC_100 3916 778.70
3 2014-03-05 ABC_100 4471 748.40
4 2014-03-06 ABC_100 5318 888.50
5 2014-03-07 ABC_100 5888 1607.10
6 2014-03-08 ABC_100 7490 2515.60
7 2014-03-09 ABC_100 4306 1569.22
8 2014-03-10 ABC_100 4939 1287.50
9 2014-03-11 ABC_100 4988 1547.00
10 2014-03-12 ABC_100 4801 1407.20
# ... with 353 more rows
This is the code I was able to write. With it I need: 1 - it breaks the dataframe into groups of 7 observations; 2 - generate the basics stats: median, variance, mean, and standard deviation of each group; 3 - store this data in a new dataframe that collects all these statistics
n <- 1
meanIBI100 <- aggregate(teste, list(rep(1:(nrow(teste) %% n+1), each = n, len = nrow(teste))), median, sd, var)[-1]
I can not make it work and I can not find ways to show me how to solve it. If anyone can help, thank you very much!
Even if someone knows how to make the loop run not only this dataframe but all the dataframes I have - and there, I believe that is the case of a loop inside another loop, I also thank you!