Of the repeated measurements of an individual in the same census, keep only the measurements (rows) taken at the highest POM (KeepMeas = "MaxHOM"), and/or the most recent measurement (same census but more recent date) (KeepMeas = "MaxDate")
Usage
UniqueMeasurement(Data, KeepMeas = c("MaxHOM", "MaxDate"), ID = "IdStem")Arguments
- Data
Dataset (data.table)
- KeepMeas
In case of multiple measurements in the same census: Possible values: "MaxHOM", "MaxDate" (character).
"MaxHOM": keep the measurement taken at the highest HOM/POM
"MaxDate": keep the most recent measurement (same census but more recent date)
- ID
Column name indicating the identifier of the individual (character)
Examples
library(data.table)
Data <- data.table( # 7 rows
IdStem = c(rep("a", 4), rep("b", 2), "c"),
IdCensus = c(rep(2000, 3), 2001, rep(2000, 3)),
Date = as.Date(c("2000-01-10", "2000-01-20", "2000-01-30", "2001-01-10",
rep("2000-01-10", 3))),
HOM = c(rep(1, 3), 2, 1, 2, 1)
)
Data
#> IdStem IdCensus Date HOM
#> <char> <num> <Date> <num>
#> 1: a 2000 2000-01-10 1
#> 2: a 2000 2000-01-20 1
#> 3: a 2000 2000-01-30 1
#> 4: a 2001 2001-01-10 2
#> 5: b 2000 2000-01-10 1
#> 6: b 2000 2000-01-10 2
#> 7: c 2000 2000-01-10 1
UniqueMeasurement(TestData)
#> MinDBH IdCensus Year Month Day Date Site Cluster Plot
#> <num> <ord> <num> <num> <num> <Date> <char> <char> <char>
#> 1: 10.03 2016 2016 9 14 2016-09-14 Paracou <NA> 6
#> 2: 10.03 2017 2017 7 19 2017-07-19 Paracou <NA> 6
#> 3: 10.03 2018 2018 7 8 2018-07-08 Paracou <NA> 6
#> 4: 10.03 2019 2019 6 7 2019-06-07 Paracou <NA> 6
#> 5: 10.03 2020 2020 6 4 2020-06-04 Paracou <NA> 6
#> ---
#> 4850: 10.03 2020 2020 6 4 2020-06-04 Paracou <NA> 6
#> 4851: 10.03 2020 2020 6 4 2020-06-04 Paracou <NA> 6
#> 4852: 10.03 2020 2020 6 4 2020-06-04 Paracou <NA> 6
#> 4853: 10.03 2020 2020 6 4 2020-06-04 Paracou <NA> 6
#> 4854: 10.03 2020 2020 6 4 2020-06-04 Paracou <NA> 6
#> PlotArea PlotElevation Subplot SubplotArea PlotViewID PlotLat PlotLon
#> <num> <num> <char> <num> <char> <num> <num>
#> 1: 6.25 NA 1 NA <NA> NA NA
#> 2: 6.25 NA 1 NA <NA> NA NA
#> 3: 6.25 NA 1 NA <NA> NA NA
#> 4: 6.25 NA 1 NA <NA> NA NA
#> 5: 6.25 NA 1 NA <NA> NA NA
#> ---
#> 4850: 6.25 NA 1 NA <NA> NA NA
#> 4851: 6.25 NA 1 NA <NA> NA NA
#> 4852: 6.25 NA 1 NA <NA> NA NA
#> 4853: 6.25 NA 1 NA <NA> NA NA
#> 4854: 6.25 NA 1 NA <NA> NA NA
#> XPlotUTM YPlotUTM SubplotLat SubplotLon XSubplotUTM YSubplotUTM
#> <num> <num> <num> <num> <num> <num>
#> 1: NA NA NA NA NA NA
#> 2: NA NA NA NA NA NA
#> 3: NA NA NA NA NA NA
#> 4: NA NA NA NA NA NA
#> 5: NA NA NA NA NA NA
#> ---
#> 4850: NA NA NA NA NA NA
#> 4851: NA NA NA NA NA NA
#> 4852: NA NA NA NA NA NA
#> 4853: NA NA NA NA NA NA
#> 4854: NA NA NA NA NA NA
#> ScientificName VernName Family Genus
#> <char> <char> <char> <char>
#> 1: Sandwithia guyanensis wata tiki Euphorbiaceae Sandwithia
#> 2: Sandwithia guyanensis wata tiki Euphorbiaceae Sandwithia
#> 3: Sandwithia guyanensis wata tiki Euphorbiaceae Sandwithia
#> 4: Sandwithia guyanensis wata tiki Euphorbiaceae Sandwithia
#> 5: Sandwithia guyanensis wata tiki Euphorbiaceae Sandwithia
#> ---
#> 4850: Gustavia hexapetala man tapuhupa Lecythidaceae Gustavia
#> 4851: Pradosia cochlearia kimboto Sapotaceae Pradosia
#> 4852: Pogonophora schomburgkiana geli koko Peraceae Pogonophora
#> 4853: Pseudolmedia laevis satine rubane Moraceae Pseudolmedia
#> 4854: Inga lomatophylla kodia weko Fabaceae Inga
#> Species Subspecies Variety Voucher IdLevel Authority CommercialSp
#> <char> <char> <char> <char> <char> <char> <lgcl>
#> 1: guyanensis <NA> <NA> <NA> <NA> <NA> FALSE
#> 2: guyanensis <NA> <NA> <NA> <NA> <NA> FALSE
#> 3: guyanensis <NA> <NA> <NA> <NA> <NA> FALSE
#> 4: guyanensis <NA> <NA> <NA> <NA> <NA> FALSE
#> 5: guyanensis <NA> <NA> <NA> <NA> <NA> FALSE
#> ---
#> 4850: hexapetala <NA> <NA> <NA> <NA> <NA> FALSE
#> 4851: cochlearia <NA> <NA> <NA> <NA> <NA> FALSE
#> 4852: schomburgkiana <NA> <NA> <NA> <NA> <NA> FALSE
#> 4853: laevis <NA> <NA> <NA> <NA> <NA> TRUE
#> 4854: lomatophylla <NA> <NA> <NA> <NA> <NA> FALSE
#> LifeForm TreeFieldNum IdTree StemFieldNum IdStem TreeLat TreeLon
#> <char> <char> <char> <char> <char> <num> <num>
#> 1: tree 1 100621 <NA> 100621_1_auto NA NA
#> 2: tree 1 100621 <NA> 100621_1_auto NA NA
#> 3: tree 1 100621 <NA> 100621_1_auto NA NA
#> 4: tree 1 100621 <NA> 100621_1_auto NA NA
#> 5: tree 1 100621 <NA> 100621_1_auto NA NA
#> ---
#> 4850: tree 3008 418631 <NA> 418631_1_auto NA NA
#> 4851: tree 3009 418632 <NA> 418632_1_auto NA NA
#> 4852: tree 3010 418633 <NA> 418633_1_auto NA NA
#> 4853: tree 3011 418634 <NA> 418634_1_auto NA NA
#> 4854: tree 3012 418635 <NA> 418635_1_auto NA NA
#> XTreeUTM YTreeUTM XTreePlot YTreePlot XTreeSubplot YTreeSubplot
#> <num> <num> <num> <num> <num> <num>
#> 1: NA NA NA NA NA NA
#> 2: NA NA NA NA NA NA
#> 3: NA NA NA NA NA NA
#> 4: NA NA NA NA NA NA
#> 5: NA NA NA NA NA NA
#> ---
#> 4850: NA NA NA NA NA NA
#> 4851: NA NA NA NA NA NA
#> 4852: NA NA NA NA NA NA
#> 4853: NA NA NA NA NA NA
#> 4854: NA NA NA NA NA NA
#> LifeStatus DeadStatus Diameter BD Circ BCirc HOM POM BHOM
#> <lgcl> <lgcl> <num> <num> <num> <num> <num> <char> <num>
#> 1: TRUE NA 13.37 NA 42.0 NA 1.3 <NA> NA
#> 2: TRUE NA 13.37 NA 42.0 NA 1.3 <NA> NA
#> 3: TRUE NA 13.37 NA 42.0 NA 1.3 <NA> NA
#> 4: TRUE NA 13.37 NA 42.0 NA 1.3 <NA> NA
#> 5: FALSE NA 13.37 NA 42.0 NA 1.3 <NA> NA
#> ---
#> 4850: TRUE NA 10.19 NA 32.0 NA 1.3 <NA> NA
#> 4851: TRUE NA 10.03 NA 31.5 NA 1.3 <NA> NA
#> 4852: TRUE NA 10.03 NA 31.5 NA 1.3 <NA> NA
#> 4853: TRUE NA 10.19 NA 32.0 NA 1.3 <NA> NA
#> 4854: TRUE NA 10.19 NA 32.0 NA 1.3 <NA> NA
#> BPOM TreeHeight TreeFieldNumOriginal IdTreeOriginal
#> <char> <num> <num> <int>
#> 1: <NA> NA 1 100621
#> 2: <NA> NA 1 100621
#> 3: <NA> NA 1 100621
#> 4: <NA> NA 1 100621
#> 5: <NA> NA 1 100621
#> ---
#> 4850: <NA> NA 3008 418631
#> 4851: <NA> NA 3009 418632
#> 4852: <NA> NA 3010 418633
#> 4853: <NA> NA 3011 418634
#> 4854: <NA> NA 3012 418635
#> CommercialSpOriginal DateOriginal LifeStatusOriginal
#> <lgcl> <char> <lgcl>
#> 1: FALSE 2016-09-14 TRUE
#> 2: FALSE 2017-07-19 TRUE
#> 3: FALSE 2018-07-08 TRUE
#> 4: FALSE 2019-06-07 TRUE
#> 5: FALSE 2020-06-04 FALSE
#> ---
#> 4850: FALSE 2020-06-04 TRUE
#> 4851: FALSE 2020-06-04 TRUE
#> 4852: FALSE 2020-06-04 TRUE
#> 4853: TRUE 2020-06-04 TRUE
#> 4854: FALSE 2020-06-04 TRUE