Hi All!

I have some experience with R, but less experience writing scripts using 
R and have run into a challenge that I hope someone can help me with.

  I have multiple .csv files of data each with the same 3 columns of 
data, but potentially of varying lengths (some data files are from short 
measurements, others from longer ones). One file for example might look 
like this...

Time, O2_conc, Chla_conc

0,270,300

10, 260, 280

20, 245, 268

30, 233, 238

40, 222, 212

50, 215, 201

60, 208, 193

70, 206, 191

80, 207,189

90, 206, 186

100, 206, 183

110, 207, 178

120, 205, 174

130, 240, 171

140, 270, 155

I am looking for an efficient means of batch (or sequentially) 
processing these files so that I can
1. import each data file

2. find the minimum value recorded in column 2 and the previous 5 data 
points

3. and average these 10 values to get a mean, minimum value.

Currently I have imported the data files using the following

filenames=list.files()

library(plyr)

import.list=adply(filenames, 1, read.csv)

and I know how to write a code to calculate the minimum value and the 5 
preceding values in a single column, in a single file. I think the 
problem I am running into is scaling this code up so that I can import 
multiple files and calculating mean, minimum value for the 2^nd column 
in each of them.

Can anyone offer some advice on how to batch processes a whole bunch of 
files? I need to load them in, but then analyze them too.

Thank you so much,

Nate


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