ls()
## character(0)
rm(list=ls())
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 366698 19.6 592000 31.7 460000 24.6
## Vcells 569072 4.4 1308461 10.0 888865 6.8
getwd()
## [1] "C:/Users/Dell/Documents/R/newproject"
pcm=c(90,72,81,89,82,NA,NA,75,70,86,NA,79,NA,94,NA,72,69)
mean(pcm)
## [1] NA
summary(pcm)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 69.00 72.00 80.00 79.92 86.75 94.00 5
mean(pcm,na.rm = TRUE)
## [1] 79.91667
pcm2=na.omit(pcm)
pcm2
## [1] 90 72 81 89 82 75 70 86 79 94 72 69
## attr(,"na.action")
## [1] 6 7 11 13 15
## attr(,"class")
## [1] "omit"
mean(pcm2)
## [1] 79.91667
is.na(pcm)
## [1] FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE
## [12] FALSE TRUE FALSE TRUE FALSE FALSE
table(is.na(pcm))
##
## FALSE TRUE
## 12 5
plot(density(pcm2))
is.na(pcm)=T
pcm3=ifelse(is.na(pcm),median(pcm,na.rm=T),pcm)
pcm3
## [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
summary(pcm)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## NA NA NA NaN NA NA 17
summary(pcm3)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## NA NA NA NaN NA NA 17
income= c("50,000","$10,00 0",20000,"30000",
25000,"100, 000",60000,"$40000",
"$50,000",90000,"50000$",
"99 000$",40000,
125000,"$45,00 0","$25,000")
mean(income)
## Warning in mean.default(income): argument is not numeric or logical:
## returning NA
## [1] NA
grepl(",",income)
## [1] TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE
## [12] FALSE FALSE FALSE TRUE TRUE
table(grepl(",",income))
##
## FALSE TRUE
## 10 6
grepl("\\$",income)
## [1] FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE
## [12] TRUE FALSE FALSE TRUE TRUE
table(grepl("\\$",income))
##
## FALSE TRUE
## 9 7
length(income)
## [1] 16
sample(16,10,F)
## [1] 4 2 16 13 10 1 11 5 14 15
b=sample(16,10,F)
income2=income[1:10]
income2=income[b]
income
## [1] "50,000" "$10,00 0" "20000" "30000" "25000"
## [6] "100, 000" "60000" "$40000" "$50,000" "90000"
## [11] "50000$" "99 000$" "40000" "125000" "$45,00 0"
## [16] "$25,000"
income2=gsub(",","",income)
income2
## [1] "50000" "$1000 0" "20000" "30000" "25000" "100 000"
## [7] "60000" "$40000" "$50000" "90000" "50000$" "99 000$"
## [13] "40000" "125000" "$4500 0" "$25000"
income3=gsub("\\$","",income2)
income3
## [1] "50000" "1000 0" "20000" "30000" "25000" "100 000"
## [7] "60000" "40000" "50000" "90000" "50000" "99 000"
## [13] "40000" "125000" "4500 0" "25000"
income3=gsub(" ","",income3)
income3
## [1] "50000" "10000" "20000" "30000" "25000" "100000" "60000"
## [8] "40000" "50000" "90000" "50000" "99000" "40000" "125000"
## [15] "45000" "25000"
income4=as.numeric(income3)
income4
## [1] 50000 10000 20000 30000 25000 100000 60000 40000 50000 90000
## [11] 50000 99000 40000 125000 45000 25000
mean(income4)
## [1] 53687.5
ls()
## [1] "b" "income" "income2" "income3" "income4" "pcm" "pcm2"
## [8] "pcm3"
list=ls()
list
## [1] "b" "income" "income2" "income3" "income4" "pcm" "pcm2"
## [8] "pcm3"
list[c(-1,-5,-9)]
## [1] "income" "income2" "income3" "pcm" "pcm2" "pcm3"
rm(list=list[c(-1,-5,-9)])
ls()
## [1] "b" "income4" "list"
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 381277 20.4 750400 40.1 592000 31.7
## Vcells 601354 4.6 1308461 10.0 1076960 8.3
ls()
## [1] "b" "income4" "list"
income4
## [1] 50000 10000 20000 30000 25000 100000 60000 40000 50000 90000
## [11] 50000 99000 40000 125000 45000 25000
length(income4)
## [1] 16
income4[17]=200000
income4
## [1] 50000 10000 20000 30000 25000 100000 60000 40000 50000 90000
## [11] 50000 99000 40000 125000 45000 25000 200000
income4[2]=200000
library(readr)
BigDiamonds <- read_csv("C:/Users/Dell/Downloads/BigDiamonds.csv (2)/BigDiamonds.csv")
## Warning: Missing column names filled in: 'X1' [1]
## Parsed with column specification:
## cols(
## X1 = col_integer(),
## carat = col_double(),
## cut = col_character(),
## color = col_character(),
## clarity = col_character(),
## table = col_double(),
## depth = col_double(),
## cert = col_character(),
## measurements = col_character(),
## price = col_integer(),
## x = col_double(),
## y = col_double(),
## z = col_double()
## )
summary(BigDiamonds)
## X1 carat cut color
## Min. : 1 Min. :0.200 Length:598024 Length:598024
## 1st Qu.:149507 1st Qu.:0.500 Class :character Class :character
## Median :299013 Median :0.900 Mode :character Mode :character
## Mean :299013 Mean :1.071
## 3rd Qu.:448518 3rd Qu.:1.500
## Max. :598024 Max. :9.250
##
## clarity table depth cert
## Length:598024 Min. : 0.00 Min. : 0.00 Length:598024
## Class :character 1st Qu.:56.00 1st Qu.:61.00 Class :character
## Mode :character Median :58.00 Median :62.10 Mode :character
## Mean :57.63 Mean :61.06
## 3rd Qu.:59.00 3rd Qu.:62.70
## Max. :75.90 Max. :81.30
##
## measurements price x y
## Length:598024 Min. : 300 Min. : 0.150 Min. : 1.000
## Class :character 1st Qu.: 1220 1st Qu.: 4.740 1st Qu.: 4.970
## Mode :character Median : 3503 Median : 5.780 Median : 6.050
## Mean : 8753 Mean : 5.991 Mean : 6.199
## 3rd Qu.:11174 3rd Qu.: 6.970 3rd Qu.: 7.230
## Max. :99990 Max. :13.890 Max. :13.890
## NA's :713 NA's :1815 NA's :1852
## z
## Min. : 0.040
## 1st Qu.: 3.120
## Median : 3.860
## Mean : 4.033
## 3rd Qu.: 4.610
## Max. :13.180
## NA's :2544
table(BigDiamonds$color)
##
## D E F G H I J K L
## 73630 93483 93573 96204 86619 70282 48709 25868 9656
Diamonds2=BigDiamonds[is.na(BigDiamonds$price),]
Diamonds3=BigDiamonds[is.na(BigDiamonds$price)==F,]
summary(Diamonds3)
## X1 carat cut color
## Min. : 494 Min. :0.200 Length:597311 Length:597311
## 1st Qu.:149842 1st Qu.:0.500 Class :character Class :character
## Median :299309 Median :0.900 Mode :character Mode :character
## Mean :299277 Mean :1.072
## 3rd Qu.:448677 3rd Qu.:1.500
## Max. :598024 Max. :9.250
##
## clarity table depth cert
## Length:597311 Min. : 0.00 Min. : 0.00 Length:597311
## Class :character 1st Qu.:56.00 1st Qu.:61.00 Class :character
## Mode :character Median :58.00 Median :62.10 Mode :character
## Mean :57.63 Mean :61.06
## 3rd Qu.:59.00 3rd Qu.:62.70
## Max. :75.90 Max. :81.30
##
## measurements price x y
## Length:597311 Min. : 300 Min. : 0.150 Min. : 1.000
## Class :character 1st Qu.: 1220 1st Qu.: 4.740 1st Qu.: 4.970
## Mode :character Median : 3503 Median : 5.780 Median : 6.050
## Mean : 8753 Mean : 5.993 Mean : 6.201
## 3rd Qu.:11174 3rd Qu.: 6.970 3rd Qu.: 7.230
## Max. :99990 Max. :13.890 Max. :13.890
## NA's :1814 NA's :1851
## z
## Min. : 0.040
## 1st Qu.: 3.120
## Median : 3.860
## Mean : 4.035
## 3rd Qu.: 4.610
## Max. :13.180
## NA's :2543
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
Diamonds21=select(Diamonds2,price,color,cut)
object.size(BigDiamonds)
## 74738272 bytes
object.size(Diamonds21)
## 15856 bytes
library(Hmisc)
## Loading required package: lattice
## Loading required package: survival
## Loading required package: Formula
## Loading required package: ggplot2
##
## Attaching package: 'Hmisc'
## The following objects are masked from 'package:dplyr':
##
## combine, src, summarize
## The following objects are masked from 'package:base':
##
## format.pval, round.POSIXt, trunc.POSIXt, units
summarize(Diamonds3$price,Diamonds3$color,median)
## Diamonds3$color Diamonds3$price
## 1 D 2690
## 2 E 2342
## 3 F 2966
## 4 G 3720
## 5 H 4535
## 6 I 4717
## 7 J 4697
## 8 K 4418
## 9 L 3017
d=summarize(Diamonds3$price,Diamonds3$color,median)
d
## Diamonds3$color Diamonds3$price
## 1 D 2690
## 2 E 2342
## 3 F 2966
## 4 G 3720
## 5 H 4535
## 6 I 4717
## 7 J 4697
## 8 K 4418
## 9 L 3017
names(d)=c("color","price")
d
## color price
## 1 D 2690
## 2 E 2342
## 3 F 2966
## 4 G 3720
## 5 H 4535
## 6 I 4717
## 7 J 4697
## 8 K 4418
## 9 L 3017
getwd()
## [1] "C:/Users/Dell/Documents/R/newproject"
write.csv(d,file="medians.csv")
head(Diamonds21)
## # A tibble: 6 × 3
## price color cut
## <int> <chr> <chr>
## 1 NA K V.Good
## 2 NA G Good
## 3 NA J Good
## 4 NA D V.Good
## 5 NA K V.Good
## 6 NA G Good
Diamonds21$newprice=NULL
Diamonds21$newprice=ifelse(Diamonds21$color=="J",4697,Diamonds21$price)
Diamonds21$newprice<-ifelse(Diamonds21$color=="D",2690,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="E",2342,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="F",2966,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="G",3720,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="H",4535,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="I",4717,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="K",4418,Diamonds21$newprice)
Diamonds21$newprice<-ifelse(Diamonds21$color=="L",3017,Diamonds21$newprice)
Diamonds21$price=ifelse(Diamonds21$color==d$color,d$price,Diamonds21$price)
## Warning in Diamonds21$color == d$color: longer object length is not a
## multiple of shorter object length
summary(Diamonds21)
## price color cut newprice
## Min. :2342 Length:713 Length:713 Min. :2342
## 1st Qu.:2966 Class :character Class :character 1st Qu.:2966
## Median :3720 Mode :character Mode :character Median :3720
## Mean :3799 Mean :3595
## 3rd Qu.:4535 3rd Qu.:4535
## Max. :4717 Max. :4717
## NA's :633
summarize(Diamonds21$newprice,Diamonds21$color,median)
## Diamonds21$color Diamonds21$newprice
## 1 D 2690
## 2 E 2342
## 3 F 2966
## 4 G 3720
## 5 H 4535
## 6 I 4717
## 7 J 4697
## 8 K 4418
## 9 L 3017
head(Diamonds21)
## # A tibble: 6 × 4
## price color cut newprice
## <dbl> <chr> <chr> <dbl>
## 1 NA K V.Good 4418
## 2 NA G Good 3720
## 3 NA J Good 4697
## 4 NA D V.Good 2690
## 5 NA K V.Good 4418
## 6 NA G Good 3720
table(is.na(Diamonds21$color))
##
## FALSE
## 713
summary(Diamonds21)
## price color cut newprice
## Min. :2342 Length:713 Length:713 Min. :2342
## 1st Qu.:2966 Class :character Class :character 1st Qu.:2966
## Median :3720 Mode :character Mode :character Median :3720
## Mean :3799 Mean :3595
## 3rd Qu.:4535 3rd Qu.:4535
## Max. :4717 Max. :4717
## NA's :633
summarize(Diamonds3$price,llist(Diamonds3$color,Diamonds3$cut),median)
## Diamonds3$color Diamonds3$cut Diamonds3$price
## 1 D Good 1970.0
## 2 D Ideal 3021.5
## 3 D V.Good 2330.0
## 4 E Good 1821.0
## 5 E Ideal 2455.0
## 6 E V.Good 2395.0
## 7 F Good 2027.0
## 8 F Ideal 3391.0
## 9 F V.Good 2800.0
## 10 G Good 2324.0
## 11 G Ideal 4353.0
## 12 G V.Good 3363.0
## 13 H Good 2756.0
## 14 H Ideal 5755.0
## 15 H V.Good 3557.0
## 16 I Good 2406.0
## 17 I Ideal 6126.0
## 18 I V.Good 3612.5
## 19 J Good 2458.0
## 20 J Ideal 5771.0
## 21 J V.Good 3462.0
## 22 K Good 2044.0
## 23 K Ideal 5793.0
## 24 K V.Good 3480.0
## 25 L Good 1550.0
## 26 L Ideal 3998.5
## 27 L V.Good 2239.0
e=summarize(Diamonds3$price,llist(Diamonds3$color,Diamonds3$cut),median)
e
## Diamonds3$color Diamonds3$cut Diamonds3$price
## 1 D Good 1970.0
## 2 D Ideal 3021.5
## 3 D V.Good 2330.0
## 4 E Good 1821.0
## 5 E Ideal 2455.0
## 6 E V.Good 2395.0
## 7 F Good 2027.0
## 8 F Ideal 3391.0
## 9 F V.Good 2800.0
## 10 G Good 2324.0
## 11 G Ideal 4353.0
## 12 G V.Good 3363.0
## 13 H Good 2756.0
## 14 H Ideal 5755.0
## 15 H V.Good 3557.0
## 16 I Good 2406.0
## 17 I Ideal 6126.0
## 18 I V.Good 3612.5
## 19 J Good 2458.0
## 20 J Ideal 5771.0
## 21 J V.Good 3462.0
## 22 K Good 2044.0
## 23 K Ideal 5793.0
## 24 K V.Good 3480.0
## 25 L Good 1550.0
## 26 L Ideal 3998.5
## 27 L V.Good 2239.0
names(e)=c("color","price")
e
## color price NA
## 1 D Good 1970.0
## 2 D Ideal 3021.5
## 3 D V.Good 2330.0
## 4 E Good 1821.0
## 5 E Ideal 2455.0
## 6 E V.Good 2395.0
## 7 F Good 2027.0
## 8 F Ideal 3391.0
## 9 F V.Good 2800.0
## 10 G Good 2324.0
## 11 G Ideal 4353.0
## 12 G V.Good 3363.0
## 13 H Good 2756.0
## 14 H Ideal 5755.0
## 15 H V.Good 3557.0
## 16 I Good 2406.0
## 17 I Ideal 6126.0
## 18 I V.Good 3612.5
## 19 J Good 2458.0
## 20 J Ideal 5771.0
## 21 J V.Good 3462.0
## 22 K Good 2044.0
## 23 K Ideal 5793.0
## 24 K V.Good 3480.0
## 25 L Good 1550.0
## 26 L Ideal 3998.5
## 27 L V.Good 2239.0
getwd()
## [1] "C:/Users/Dell/Documents/R/newproject"
write.csv(e,file="medianscuts.csv")
Diamonds21$newprice2=ifelse(Diamonds21$color=="D"&Diamonds21$cut=="Good",1970,Diamonds21$price)
Diamonds21$newprice2=ifelse(Diamonds21$color=="D"&Diamonds21$cut=="Ideal",3021.5,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="D"&Diamonds21$cut=="V.Good",2330,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="E"&Diamonds21$cut=="Good",1821,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="E"&Diamonds21$cut=="Ideal",2455,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="E"&Diamonds21$cut=="V.Good",2395,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="F"&Diamonds21$cut=="Good",2027,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="F"&Diamonds21$cut=="Ideal",3391,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="F"&Diamonds21$cut=="V.Good",2800,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="G"&Diamonds21$cut=="Good",2324,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="G"&Diamonds21$cut=="Ideal",4353,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="G"&Diamonds21$cut=="V.Good",3363,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="H"&Diamonds21$cut=="Good",2756,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="H"&Diamonds21$cut=="Ideal",5755,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="H"&Diamonds21$cut=="V.Good",3557,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="I"&Diamonds21$cut=="Good",2406,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="I"&Diamonds21$cut=="Ideal",6126,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="I"&Diamonds21$cut=="V.Good",3612.5,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="J"&Diamonds21$cut=="Good",2458,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="J"&Diamonds21$cut=="Ideal",5771,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="J"&Diamonds21$cut=="V.Good",3462,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="K"&Diamonds21$cut=="Good",2044,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="K"&Diamonds21$cut=="Ideal",5793,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="K"&Diamonds21$cut=="V.Good",3480,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="L"&Diamonds21$cut=="Good",1550,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="L"&Diamonds21$cut=="Ideal",3998.5,Diamonds21$newprice2)
Diamonds21$newprice2=ifelse(Diamonds21$color=="L"&Diamonds21$cut=="V.Good",2239,Diamonds21$newprice2)
summarize(Diamonds21$newprice2,llist(Diamonds21$cut,Diamonds21$color),median)
## Diamonds21$cut Diamonds21$color Diamonds21$newprice2
## 1 Good D 1970.0
## 2 Good E 1821.0
## 3 Good F 2027.0
## 4 Good G 2324.0
## 5 Good H 2756.0
## 6 Good I 2406.0
## 7 Good J 2458.0
## 8 Good K 2044.0
## 9 Good L 1550.0
## 10 Ideal D 3021.5
## 11 Ideal E 2455.0
## 12 Ideal F 3391.0
## 13 Ideal G 4353.0
## 14 Ideal H 5755.0
## 15 Ideal I 6126.0
## 16 Ideal J 5771.0
## 17 Ideal K 5793.0
## 18 V.Good D 2330.0
## 19 V.Good E 2395.0
## 20 V.Good F 2800.0
## 21 V.Good G 3363.0
## 22 V.Good H 3557.0
## 23 V.Good I 3612.5
## 24 V.Good J 3462.0
## 25 V.Good K 3480.0
## 26 V.Good L 2239.0
Diamonds21
## # A tibble: 713 × 5
## price color cut newprice newprice2
## <dbl> <chr> <chr> <dbl> <dbl>
## 1 NA K V.Good 4418 3480
## 2 NA G Good 3720 2324
## 3 NA J Good 4697 2458
## 4 NA D V.Good 2690 2330
## 5 NA K V.Good 4418 3480
## 6 NA G Good 3720 2324
## 7 NA G Good 3720 2324
## 8 NA D V.Good 2690 2330
## 9 NA K V.Good 4418 3480
## 10 NA F Good 2966 2027
## # ... with 703 more rows
attach(Diamonds21)
boxplot(BigDiamonds$price~BigDiamonds$color)
hist(BigDiamonds$price)
barplot(BigDiamonds$price)
#plot(density(BigDiamonds$price))
data(anscombe)
lapply(anscombe,mean)
## $x1
## [1] 9
##
## $x2
## [1] 9
##
## $x3
## [1] 9
##
## $x4
## [1] 9
##
## $y1
## [1] 7.500909
##
## $y2
## [1] 7.500909
##
## $y3
## [1] 7.5
##
## $y4
## [1] 7.500909
lapply(anscombe,sd)
## $x1
## [1] 3.316625
##
## $x2
## [1] 3.316625
##
## $x3
## [1] 3.316625
##
## $x4
## [1] 3.316625
##
## $y1
## [1] 2.031568
##
## $y2
## [1] 2.031657
##
## $y3
## [1] 2.030424
##
## $y4
## [1] 2.030579
data(mtcars)
table(mtcars$mpg)
##
## 10.4 13.3 14.3 14.7 15 15.2 15.5 15.8 16.4 17.3 17.8 18.1 18.7 19.2 19.7
## 2 1 1 1 1 2 1 1 1 1 1 1 1 2 1
## 21 21.4 21.5 22.8 24.4 26 27.3 30.4 32.4 33.9
## 2 2 1 2 1 1 1 2 1 1
table(mtcars$cyl)
##
## 4 6 8
## 11 7 14
table(mtcars$gear)
##
## 3 4 5
## 15 12 5
table(mtcars$cyl,mtcars$gear)
##
## 3 4 5
## 4 1 8 2
## 6 2 4 1
## 8 12 0 2
library(Hmisc)
summarize(mtcars$mpg,llist(mtcars$cyl,mtcars$gear),mean)
## mtcars$cyl mtcars$gear mtcars$mpg
## 1 4 3 21.500
## 2 4 4 26.925
## 3 4 5 28.200
## 4 6 3 19.750
## 5 6 4 19.750
## 6 6 5 19.700
## 7 8 3 15.050
## 8 8 5 15.400
with(mtcars, tapply(mpg, list(cyl,gear), FUN= mean))
## 3 4 5
## 4 21.50 26.925 28.2
## 6 19.75 19.750 19.7
## 8 15.05 NA 15.4
library(reshape2)
acast(mtcars, cyl~gear, value.var='mpg', mean)
## 3 4 5
## 4 21.50 26.925 28.2
## 6 19.75 19.750 19.7
## 8 15.05 NaN 15.4