r$> iris %>% .[which(as.numeric(rownames(.))%%3!=0),] %>% rownames
[1] "1" "2" "4" "5" "7" "8" "10" "11" "13" "14" "16" "17" "19" "20" "22" "23" "25" "26" "28" "29" "31" "32" "34" "35" "37" "38" "40" "41" "43" "44" "46"
[32] "47" "49" "50" "52" "53" "55" "56" "58" "59" "61" "62" "64" "65" "67" "68" "70" "71" "73" "74" "76" "77" "79" "80" "82" "83" "85" "86" "88" "89" "91" "92"
[63] "94" "95" "97" "98" "100" "101" "103" "104" "106" "107" "109" "110" "112" "113" "115" "116" "118" "119" "121" "122" "124" "125" "127" "128" "130" "131" "133" "134" "136" "137" "139"
[94] "140" "142" "143" "145" "146" "148" "149"
r$> iris %>% .[which(as.numeric(rownames(.))%%3!=0),] %>% mutate(Sepal.Length=Sepal.Length+1) %>% rownames
[1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" "31"
[32] "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60" "61" "62"
[63] "63" "64" "65" "66" "67" "68" "69" "70" "71" "72" "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84" "85" "86" "87" "88" "89" "90" "91" "92" "93"
[94] "94" "95" "96" "97" "98" "99" "100"
I like mutate(),because it's easy to use in pipe. As above example,you can find rownames changed after mutate.
I need to mutate columns but keep the rowname not changed,how to do it through R pipe?
That is because mutate or in general dplyr readjusts rownames from 1 after any operation hence, it does not maintain the original rownames.
If you need them for further manipulation store them as a column.
library(dplyr)
iris %>%
.[which(as.numeric(rownames(.))%%3!=0),] %>%
mutate(row = rownames(.),
Sepal.Length=Sepal.Length+1) %>%
pull(row)
# [1] "1" "2" "4" "5" "7" "8" "10" "11" "13" "14" "16" "17" "19" "20" "22" "23" "25" "26"
# [19] "28" "29" "31" "32" "34" "35" "37" "38" "40" "41" "43" "44" "46" "47" "49" "50" "52" "53"
# [37] "55" "56" "58" "59" "61" "62" "64" "65" "67" "68" "70" "71" "73" "74" "76" "77" "79" "80"
# [55] "82" "83" "85" "86" "88" "89" "91" "92" "94" "95" "97" "98" "100" "101" "103" "104" "106" "107"
# [73] "109" "110" "112" "113" "115" "116" "118" "119" "121" "122" "124" "125" "127" "128" "130" "131" "133" "134"
# [91] "136" "137" "139" "140" "142" "143" "145" "146" "148" "149"
iris %>% tibble::rownames_to_column(., 'rowname') %>% .[which(as.numeric(rownames(.))%%3!=0),] %>% mutate(Sepal.Length=Sepal.Length+1) %>% tibble::column_to_rownames(.,'rowname')
Having rownames goes against dplyr's dataframe structure principles. See Hadley's reasoning here.
Best workaround if you want to stick to dplyr is to first store the rownames as a column using rownames_to_column, do your manipulation, then reinstate the rownames using column_to_rownames (both functions are from the tibble package).
Using your example:
library(dplyr)
library(tibble)
iris %>%
.[which(as.numeric(rownames(.))%%3!=0),] %>%
# store rownames in a column
rownames_to_column(var = "rowid") %>%
# dplyr manipulation
mutate(Sepal.Length=Sepal.Length+1) %>%
# reinstate rownames
column_to_rownames(var = "rowid") %>%
# check rownames
rownames()
# [1] "1" "2" "4" "5" "7" "8" "10" "11" "13" "14" "16" "17" "19" "20" "22" "23" "25" "26" "28" "29" "31" "32" "34" "35" "37" "38"
# [27] "40" "41" "43" "44" "46" "47" "49" "50" "52" "53" "55" "56" "58" "59" "61" "62" "64" "65" "67" "68" "70" "71" "73" "74" "76" "77"
# [53] "79" "80" "82" "83" "85" "86" "88" "89" "91" "92" "94" "95" "97" "98" "100" "101" "103" "104" "106" "107" "109" "110" "112" "113" "115" "116"
# [79] "118" "119" "121" "122" "124" "125" "127" "128" "130" "131" "133" "134" "136" "137" "139" "140" "142" "143" "145" "146" "148" "149"
Related
Let us suppose to have C<-c(1,2,3,4,5)
I want to find all the unique couples of numbers that can be extracted from this vector, e.g.,12,13 23 etc. How can I do it?
One option could be:
na.omit(c(`diag<-`(sapply(x, paste0, x), NA)))
[1] "12" "13" "14" "15" "21" "23" "24" "25" "31" "32" "34" "35" "41" "42" "43" "45"
[17] "51" "52" "53" "54"
Using RcppAlgos package.
## Combinations
unlist(RcppAlgos::comboGeneral(x, 2, FUN=function(x) Reduce(paste0, x)))
# [1] "12" "13" "14" "15" "23" "24" "25" "34" "35" "45"
## Permutations
unlist(RcppAlgos::permuteGeneral(x, 2, FUN=function(x) Reduce(paste0, x)))
# [1] "12" "13" "14" "15" "21" "23" "24" "25" "31" "32" "34" "35" "41" "42" "43"
# [16] "45" "51" "52" "53" "54"
Below is my DTM type data set:
View(sms_dtm_freq_train)
sms_dtm_freq_train[["dimnames"]]
$Docs
[1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14"
[15] "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28"
[29] "29" "30" "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42"
[43] "43" "44" "45" "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56"
[57] "57" "58" "59" "60" "61" "62" "63" "64" "65" "66" "67" "68" "69" "70"
[71] "71" "72" "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84"
[85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96" "97" "98"
[99] "99" "100" "101" "102" "103" "104" "105" "106" "107" "108" "109" "110" "111" "112"
..........
[ reached getOption("max.print") -- omitted 4057 entries ]
$Terms
[1] "â£wk" "…" "–" "abiola" "abl" "abt"
[7] "accept" "access" "account" "across" "activ" "actual"
[13] "add" "address" "admir" "adult" "advanc" "aft"
[19] "afternoon" "aftr" "age" "ago" "ahead" "aight"
[25] "aint" "air" "aiyah" "alex" "almost" "alon"
[31] "alreadi" "alright" "alrit" "also" "alway" "amp"
[37] "angri" "announc" "anoth" "answer" "anybodi" "anymor"
[43] "anyon" "anyth" "anytim" "anyway" "apart" "app"
[49] "appli" "appoint" "appreci" "april" "ard" "area"
[55] "argument" "arm" "around" "arrang" "arrest" "arriv"
[61] "asap" "ask" "askd" "asleep" "ass" "attempt"
[67] "auction" "avail" "ave" "avoid" "await" "award"
[73] "away" "awesom" "babe" "babi" "back" "bad"
[79] "bag" "bak" "balanc" "bank" "bare" "bath"
[85] "batteri" "bcoz" "bcum" "bday" "beauti" "becom"
[91] "bed" "bedroom" "begin" "believ" "belli" "best"
[97] "better" "bid" "big" "bill" "bird" "birthday"
..............
[ reached getOption("max.print") -- omitted 1057 entries ]
When i run:
sms_train <- apply(sms_dtm_freq_train, MARGIN = 2, convert_counts)
I got the error messages below:
Error in apply(sms_dtm_freq_train, MARGIN = 2, convert_counts) :
dim(X) must have a positive length
I type the same codes as the text book "Machine Learning with R" 's , but i got the errors.
I am very confused.
Anyone can help me solve this problem ?
Thanks!
I want to write a function that will split a dataframe to train, cross-validation and test sets.
My code is the following, exemplified by a small dataset:
library(ISLR)
library(data.table)
data <- Auto
seed <- 12
train <- 0.7
test <- 0.6
# Function_split_test_train_regression <- function(data, train, test, seed){
set.seed(seed)
setDT(data)
data[, index := row.names(data)]
train_index <- sample(data$index, train * nrow(data))
test_index <- ifelse(test == 1, setdiff(data$index, train_index),
sample(setdiff(data$index, train_index), test * length(setdiff(data$index, train_index))))
# etc
#}
At this point I make some checks and I get a surprising to me result:
> test == 1
[1] FALSE
> sample(setdiff(data$index, train_index),
test * length(setdiff(data$index, train_index)))
[1] "225" "186" "41" "381" "356" "178" "147" "158" "21" "259" "207" "159" "250" "167" "128" "218" "271" "197" "376" "19" "77"
[22] "205" "46" "3" "212" "238" "61" "11" "68" "130" "200" "274" "127" "305" "201" "32" "48" "184" "290" "349" "155" "370"
[43] "366" "333" "243" "161" "108" "65" "125" "306" "357" "189" "337" "118" "364" "6" "149" "87" "252" "194" "362" "383" "93"
[64] "38" "18" "322" "220" "307" "60" "353"
> test_index <- ifelse(test == 1, setdiff(data$index, train_index),
sample(setdiff(data$index, train_index),
test * length(setdiff(data$index, train_index))))
> test_index
[1] "219"
Why iflese returns 219 rather than the value of the second argument (since the condition test == 1 evaluates to FALSE) ?
Your advice will be appreciated.
================================================================================
EDIT
Following the suggestion made in the comments I changed the code replacing the name test with the name test_fraction but the problem remained. The new code:
library(ISLR)
library(data.table)
data <- Auto
seed <- 12
train_fraction <- 0.7
test_fraction <- 0.6
# Function_split_test_crossval_train_regr <- function(data, train, test, seed){
set.seed(seed)
setDT(data)
data[, index := row.names(data)]
train_index <- sample(data$index, train_fraction * nrow(data))
test_index <- ifelse(test_fraction == 1, setdiff(data$index, train_index), sample(setdiff(data$index, train_index),
test_fraction * length(setdiff(data$index, train_index))))
#}
The results:
> train_index
[1] "119" "118" "143" "344" "293" "341" "305" "95" "82" "58" "226" "35" "363" "111" "84" "137" "24" "151" "381" "110" "93"
[22] "198" "133" "6" "112" "228" "62" "36" "165" "353" "271" "385" "322" "291" "316" "268" "333" "37" "377" "176" "343" "281"
[43] "245" "75" "238" "183" "215" "68" "274" "64" "224" "391" "26" "83" "66" "308" "1" "372" "161" "170" "300" "52" "30"
[64] "15" "57" "148" "312" "311" "194" "367" "27" "342" "260" "181" "163" "171" "193" "210" "327" "248" "172" "263" "47" "351"
[85] "166" "292" "278" "61" "116" "204" "309" "200" "96" "330" "383" "346" "249" "368" "41" "38" "235" "4" "77" "273" "191"
[106] "212" "99" "31" "286" "79" "184" "284" "267" "374" "355" "358" "124" "114" "335" "70" "203" "379" "14" "287" "67" "34"
[127] "340" "127" "91" "222" "240" "387" "357" "242" "310" "347" "142" "103" "105" "117" "189" "361" "177" "126" "392" "5" "317"
[148] "174" "352" "87" "234" "147" "202" "261" "277" "214" "290" "339" "109" "43" "120" "169" "318" "56" "94" "115" "314" "320"
[169] "276" "237" "296" "307" "23" "186" "360" "146" "313" "152" "206" "328" "60" "195" "69" "107" "97" "92" "325" "20" "362"
[190] "157" "101" "10" "192" "134" "251" "259" "2" "29" "265" "331" "144" "63" "384" "81" "338" "364" "213" "380" "150" "48"
[211] "54" "354" "187" "283" "356" "389" "72" "32" "121" "376" "33" "359" "349" "239" "241" "232" "196" "74" "156" "201" "390"
[232] "326" "285" "51" "131" "304" "85" "45" "336" "280" "178" "128" "98" "275" "246" "65" "39" "188" "55" "90" "197" "9"
[253] "173" "40" "295" "149" "230" "140" "135" "236" "21" "369" "301" "220" "122" "253" "208" "388" "159" "282" "88" "158" "167"
[274] "257"
> sample(setdiff(data$index, train_index),
+ test_fraction * length(setdiff(data$index, train_index)))
[1] "337" "378" "164" "225" "16" "44" "221" "179" "25" "28" "324" "175" "139" "154" "17" "252" "211" "155" "233" "162" "130"
[22] "216" "255" "190" "365" "373" "73" "207" "42" "3" "348" "227" "49" "12" "53" "315" "199" "256" "129" "375" "205" "18"
[43] "289" "168" "264" "160" "145" "382" "136" "302" "185" "323" "100" "270" "113" "294" "247" "345" "209" "104" "321" "7" "138"
[64] "78" "386" "366" "298" "231" "86" "19"
> test_fraction == 1
[1] FALSE
> test_index <- ifelse(test_fraction == 1, setdiff(data$index, train_index), sample(setdiff(data$index, train_index),
+ test_fraction * length(setdiff(data$index, train_index))))
> test_index
[1] "28"
I have no idea why this is happening, I hope someone come with an explanation.
But I found a solution to your problem. You need to pass the arguments to the object inside the ifelse():
ifelse(
test_fraction == 1,
test_index <- setdiff(data$index, train_index),
test_index <- sample(setdiff(data$index, train_index),test_fraction * length(setdiff(data$index, train_index)))
)
I don't if this is bad practice or not, but it works. It also can be used to assign multiple conditions in the conditions like my answer here.
I have a data.table with many missing values and I want a variable which gives me a 1 for the first non-missin value in each group.
Say I have such a data.table:
library(data.table)
DT <- data.table(iris)[,.(Petal.Width,Species)]
DT[c(1:10,15,45:50,51:70,101:134),Petal.Width:=NA]
which now has missings in the beginning, at the end and in between. I have tried two versions, one is:
DT[min(which(!is.na(Petal.Width))),first_available:=1,by=Species]
but it only finds the global minimum (in this case, setosa gets the correct 1), not the minimum by group. I think this is the case because data.table first subsets by i, then sorts by group, correct? So it will only work with the row that is the global minimum of which(!is.na(Petal.Width)) which is the first non-NA value.
A second attempt with the test in j:
DT[,first_available:= ifelse(min(which(!is.na(Petal.Width))),1,0),by=Species]
which just returns a column of 1s. Here, I don't have a good explanation as to why it doesn't work.
my goal is this:
DT[,first_available:=0]
DT[c(11,71,135),first_available:=1]
but in reality I have hundreds of groups. Any help would be appreciated!
Edit: this question does come close but is not targeted at NA's and does not solve the issue here if I understand it correctly. I tried:
DT <- data.table(DT, key = c('Species'))
DT[unique(DT[,key(DT), with = FALSE]), mult = 'first']
Here's one way:
DT[!is.na(Petal.Width), first := as.integer(seq_len(.N) == 1L), by = Species]
We can try
DT[DT[, .I[which.max(!is.na(Petal.Width))] , Species]$V1,
first_available := 1][is.na(first_available), first_available := 0]
Or a slightly more compact option is
DT[, first_available := as.integer(1:nrow(DT) %in%
DT[, .I[!is.na(Petal.Width)][1L], by = Species]$V1)][]
> DT[!is.na(DT$Petal.Width) & DT$first_available == 1]
# Petal.Width Species first_available
# 1: 0.2 setosa 1
# 2: 1.8 versicolor 1
# 3: 1.4 virginica 1
> rownames(DT)[!is.na(DT$Petal.Width) & DT$first_available == 1]
# [1] "11" "71" "135"
> rownames(DT)[!is.na(DT$Petal.Width) & DT$first_available == 0]
# [1] "12" "13" "14" "16" "17" "18" "19" "20" "21" "22" "23" "24"
# [13] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36"
# [25] "37" "38" "39" "40" "41" "42" "43" "44" "72" "73" "74" "75"
# [37] "76" "77" "78" "79" "80" "81" "82" "83" "84" "85" "86" "87"
# [49] "88" "89" "90" "91" "92" "93" "94" "95" "96" "97" "98" "99"
# [61] "100" "136" "137" "138" "139" "140" "141" "142" "143" "144" "145" "146"
# [73] "147" "148" "149" "150"
I have a variable in my dataset for which there are about 2000 factor levels, but many of the levels are quite similar:
"7" "BE Classifieds - Village Voice - Display"
"8" "Bridgevine Online"
"9" "British Columbia BNE - Group 1"
"10" "British Columbia BNE - Group 10"
"11" "British Columbia BNE - Group 11"
"12" "British Columbia BNE - Group 12"
"13" "British Columbia BNE - Group 13"
"14" "British Columbia BNE - Group 14"
"15" "British Columbia BNE - Group 2"
"16" "British Columbia BNE - Group 3"
"17" "British Columbia BNE - Group 4"
"18" "British Columbia BNE - Group 5"
"19" "British Columbia BNE - Group 6"
"20" "British Columbia BNE - Group 7"
"21" "British Columbia BNE - Group 8"
"22" "British Columbia BNE - Group 9"
"23" "buyjustenergydefault"
"24" "C2CBetaBrands"
"25" "C2CBetaElectrcity"
"26" "C2CBetaJE-ES"
"27" "CallerID Callback - Energy Savings"
"28" "Choose Energy Transfers"
"29" "Choose Energy Warm Transfers"
"30" "Clear Corporate Teletech Telesales Transfer to JE"
"31" "Clear Internet Live Transfer - TX, GA"
"32" "Clear Internet Transfer - Non-ISTA"
"33" "commenergy"
"34" "Commercial to Residential Transfer"
"35" "Coreg"
"36" "Customer Service-Energy Savings"
"37" "CW Leads - Non transfer (ISTA)"
"38" "CW Leads - Non transfer (Non-ISTA)"
"39" "D* Just Clean In-Line"
"40" "D* Transfer - Scripting Test"
"41" "Default/Unknown Program"
"42" "DirectStar Live Transfer - Retentions"
"43" "DStar (FC) Transfer"
"44" "DStar Leads - Non transfer (ISTA)"
"45" "DStar Leads - Non transfer (Non-ISTA)"
"46" "DStar Outbound Friends and Family"
"47" "Dstar to Energy Georgia Transfer"
"48" "DStar Transfer - Non-ISTA"
"49" "DStar Transfer - TX, GA"
"50" "electricdotcomwebsitedefault"
"51" "ES-AEP-HAILO-GOOG-DTOP-Competitors-AB"
"52" "ES-AEP-HAILO-GOOG-DTOP-Nonbrand-AB"
"53" "ES-AEP-HAILO-GOOG-MOBI-NT-Competitor-AB"
"54" "ES-AEP-HAILO-GOOG-MOBI-NT-Competitors-AB-Unspecified"
"55" "ES-AEP-HAILO-GOOG-MOBI-NT-Nonbrand-AB"
"56" "es-albertaenergyprovidersca-webdefault"
"57" "ES-CEDS-HAILO-GOOG-DTOP-Brand-GA"
"58" "ES-CEDS-HAILO-GOOG-DTOP-Brand-NJ"
"59" "ES-CEDS-HAILO-GOOG-DTOP-Brand-PA"
"60" "ES-CEDS-HAILO-GOOG-DTOP-Competitors-GA"
"61" "ES-CEDS-HAILO-GOOG-DTOP-Competitors-NJ"
"62" "ES-CEDS-HAILO-GOOG-DTOP-Content-GA"
"63" "ES-CEDS-HAILO-GOOG-DTOP-NonBrand-GA"
"64" "ES-CEDS-HAILO-GOOG-DTOP-Nonbrand-NJ"
"65" "ES-CEDS-HAILO-GOOG-DTOP-Nonbrand-PA"
"66" "ES-CEDS-HAILO-GOOG-MOBI-NT-Brand-GA"
"67" "ES-CEDS-HAILO-GOOG-MOBI-NT-Brand-NJ"
"68" "ES-CEDS-HAILO-GOOG-MOBI-NT-Brand-PA"
"69" "ES-CEDS-HAILO-GOOG-MOBI-NT-Competitors-GA"
"70" "ES-CEDS-HAILO-GOOG-MOBI-NT-Competitors-GA-Unspecified"
"71" "ES-CEDS-HAILO-GOOG-MOBI-NT-Competitors-NJ"
"72" "ES-CEDS-HAILO-GOOG-MOBI-NT-Competitors-NJ-Unspecified"
"73" "ES-CEDS-HAILO-GOOG-MOBI-NT-Competitors-PA"
"74" "ES-CEDS-HAILO-GOOG-MOBI-NT-Nonbrand-GA"
"75" "ES-CEDS-HAILO-GOOG-MOBI-NT-Nonbrand-NJ"
"76" "ES-CEDS-HAILO-GOOG-MOBI-NT-Nonbrand-PA"
"77" "ES-CEDS-HAILO-MSN-DTOP-Brand-GA"
"78" "ES-CEDS-HAILO-MSN-DTOP-Brand-NJ"
"79" "ES-CEDS-HAILO-MSN-DTOP-Brand-PA"
"80" "ES-CEDS-HAILO-MSN-DTOP-Competitors-GA"
"81" "ES-CEDS-HAILO-MSN-DTOP-Competitors-NJ"
"82" "ES-CEDS-HAILO-MSN-DTOP-Nonbrand-GA"
"83" "ES-CEDS-HAILO-MSN-DTOP-Nonbrand-NJ"
"84" "ES-CEDS-HAILO-MSN-DTOP-Nonbrand-PA"
"85" "ES-EYSG-HAILO-GOOG-DTOP-Competitors-NY"
"86" "ES-EYSG-HAILO-GOOG-DTOP-Competitors-TX"
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So I'm wondering how to combine all of the levels that start with a certain prefix, say "British Columbia BNE" - ....
I've looked into combine.levels and varclus but I don't think these are the right commands...is there a way to combine by prefix?
I figured it out. Use idx = grep(prefix, data.frame) to get the indices and then
data.frame[idx] = blah