[R] data.frame: data-driven column selections that vary by row??
David Wolfskill
r at catwhisker.org
Tue Mar 31 19:22:09 CEST 2015
On Tue, Mar 31, 2015 at 07:11:28AM -0800, John Kane wrote:
> I think we need some data and code
> Reproducibility
> https://github.com/hadley/devtools/wiki/Reproducibility
> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
> ....
I apologize for failing to provide that.
Here is a quite small subset of the data (with a few edits to reduce
excess verbosity in names of things) that still illustrates the
challenge I perceive:
> dput(bw)
structure(list(timestamp = c(1426892400L, 1426892400L, 1426892400L,
1426892400L, 1426892400L, 1426892400L, 1426892460L, 1426892460L,
1426892460L, 1426892460L, 1426892460L, 1426892460L, 1426892520L,
1426892520L, 1426892520L, 1426892520L, 1426892520L, 1426892520L
), hostname = c("c001", "c002", "c021", "c022", "c041", "c051",
"c001", "c002", "c021", "c022", "c041", "c051", "c001", "c002",
"c021", "c022", "c041", "c051"), health = c(0.0549374999999983,
0.250585416666667, 1, 1, 0.577784167075767, 0.546805261621527,
0.1599375, 0.24954375, 1, 1, 0.582307554123614, 0.558298168996525,
0.2813125, 0.270877083333333, 1, 1, 0.579231349457365, 0.542973020177151
), hw = c(1.9, 1.9, 1.4, 1.4, 1.5, 1.5, 1.9, 1.9, 1.4, 1.4, 1.5,
1.5, 1.9, 1.9, 1.4, 1.4, 1.5, 1.5), fw = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), .Label = "2015Q1.2", class = "factor"), role = structure(c(1L,
2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L,
2L), .Label = c("control", "test"), class = "factor"), type = structure(c(3L,
3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L,
2L), .Label = c("D", "F", "H"), class = "factor"), da20_busy_pct = c(79.1,
62.8, NA, NA, NA, NA, 75, 64.8, NA, NA, NA, NA, 72.2, 74.5, NA,
NA, NA, NA), da20_dev_type = structure(c(2L, 2L, 1L, 1L, 1L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L), .Label = c("",
"hdd"), class = "factor"), da20_kb_per_xfer_read = c(727.23,
665.81, NA, NA, NA, NA, 737.04, 691.38, NA, NA, NA, NA, 721.71,
668.96, NA, NA, NA, NA), da20_kb_per_xfer_write = c(0, 0, NA,
NA, NA, NA, 0, 0, NA, NA, NA, NA, 0, 0, NA, NA, NA, NA), da20_mb_per_sec_read = c(39.77,
31.21, NA, NA, NA, NA, 36.71, 32.41, NA, NA, NA, NA, 35.94, 37.24,
NA, NA, NA, NA), da20_mb_per_sec_write = c(0, 0, NA, NA, NA,
NA, 0, 0, NA, NA, NA, NA, 0, 0, NA, NA, NA, NA), da20_ms_per_xactn_read = c(43.5,
31.6, NA, NA, NA, NA, 35.7, 30.2, NA, NA, NA, NA, 32.7, 34.6,
NA, NA, NA, NA), da20_ms_per_xactn_write = c(0, 0, NA, NA, NA,
NA, 0, 0, NA, NA, NA, NA, 0, 0, NA, NA, NA, NA), da20_Q_length = c(0,
0, NA, NA, NA, NA, 2, 0, NA, NA, NA, NA, 1, 1, NA, NA, NA, NA
), da20_xfers_per_sec_other = c(0, 0, NA, NA, NA, NA, 0, 0, NA,
NA, NA, NA, 0, 0, NA, NA, NA, NA), da20_xfers_per_sec_read = c(56,
48, NA, NA, NA, NA, 51, 48, NA, NA, NA, NA, 51, 57, NA, NA, NA,
NA), da20_xfers_per_sec_write = c(0, 0, NA, NA, NA, NA, 0, 0,
NA, NA, NA, NA, 0, 0, NA, NA, NA, NA), da2_busy_pct = c(84.5,
81.8, 29.5, 26.7, 55.5, 50.9, 80.6, 79.7, 29.2, 27.3, 58.8, 50.2,
74.6, 79.3, 29.4, 26.6, 55.4, 50.1), da2_dev_type = structure(c(2L,
2L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L, 3L, 2L, 2L, 3L, 3L, 3L,
3L), .Label = c("", "hdd", "ssd"), class = "factor"), da2_kb_per_xfer_read = c(690.67,
686.63, 613.78, 587, 571.64, 553.27, 692.26, 660.05, 612.01,
594.28, 560.16, 566.41, 672.68, 670.25, 604.64, 592.16, 565.02,
564.43), da2_kb_per_xfer_write = c(0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0), da2_mb_per_sec_read = c(44.52, 41.57,
134.26, 120.38, 252.88, 229.09, 41.24, 39.96, 132.68, 123.61,
268.04, 227.34, 37.44, 39.93, 133.45, 120.28, 251.06, 225.99),
da2_mb_per_sec_write = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0), da2_ms_per_xactn_read = c(49.1, 47.8,
2, 1.8, 2.6, 2.4, 40.3, 43.9, 2, 1.8, 2.8, 2.4, 37.1, 40.9,
1.9, 1.8, 2.6, 2.4), da2_ms_per_xactn_write = c(0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), da2_Q_length = c(0,
2, 0, 1, 3, 0, 3, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 3), da2_xfers_per_sec_other = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), da2_xfers_per_sec_read = c(66,
62, 224, 210, 453, 424, 61, 62, 222, 213, 490, 411, 57, 61,
226, 208, 455, 410), da2_xfers_per_sec_write = c(0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), .Names = c("timestamp",
"hostname", "health", "hw", "fw", "role", "type", "da20_busy_pct",
"da20_dev_type", "da20_kb_per_xfer_read", "da20_kb_per_xfer_write",
"da20_mb_per_sec_read", "da20_mb_per_sec_write", "da20_ms_per_xactn_read",
"da20_ms_per_xactn_write", "da20_Q_length", "da20_xfers_per_sec_other",
"da20_xfers_per_sec_read", "da20_xfers_per_sec_write", "da2_busy_pct",
"da2_dev_type", "da2_kb_per_xfer_read", "da2_kb_per_xfer_write",
"da2_mb_per_sec_read", "da2_mb_per_sec_write", "da2_ms_per_xactn_read",
"da2_ms_per_xactn_write", "da2_Q_length", "da2_xfers_per_sec_other",
"da2_xfers_per_sec_read", "da2_xfers_per_sec_write"), class = "data.frame", row.names = c(1L,
2L, 7L, 8L, 13L, 16L, 19L, 20L, 25L, 26L, 31L, 34L, 37L, 38L,
43L, 44L, 49L, 52L))
> dim(bw)
[1] 18 31
(In the current case, there are a few more columns per device, as
well as about 40 more devices -- and thousands of rows -- represented
in the data.)
For reference (as well):
> version
_
platform i386-portbld-freebsd10.1
arch i386
os freebsd10.1
system i386, freebsd10.1
status Patched
major 3
minor 0.2
year 2013
month 11
day 12
svn rev 64207
language R
version.string R version 3.0.2 Patched (2013-11-12 r64207)
nickname Frisbee Sailing
>
[BTW: the first link cited (above) is now a redirect to
<http://adv-r.had.co.nz/Reproducibility.html>.]
Peace,
david
--
David H. Wolfskill r at catwhisker.org
Those who murder in the name of God or prophet are blasphemous cowards.
See http://www.catwhisker.org/~david/publickey.gpg for my public key.
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