Poskusni dokument
A Blejec
06 junij 2017
Branje podatkov
Podatke bomo prebrali iz datoteke, ki je shranjena na spletu.
fpath <- "http://bit.ly/16oBVpR"
data <- read.table(fpath,header=TRUE,sep="\t")
dim(data)## [1] 43 12names(data)## [1] "starost" "mesec" "spol" "masa" "visina" "roke" "cevelj"
## [8] "lasje" "oci" "mati" "oce" "majica"Podatki so prebrani !!
Povzetek podatkov
Poglejmo, kako so porazdeljeni podatki
summary(data)## starost mesec spol masa visina
## Min. :20.00 Min. : 0.000 F:33 Min. :50.00 Min. :156.0
## 1st Qu.:21.00 1st Qu.: 5.000 M:10 1st Qu.:55.50 1st Qu.:164.0
## Median :21.00 Median : 7.000 Median :61.00 Median :170.0
## Mean :22.07 Mean : 6.814 Mean :63.42 Mean :169.9
## 3rd Qu.:22.00 3rd Qu.: 9.500 3rd Qu.:70.00 3rd Qu.:173.5
## Max. :59.00 Max. :11.000 Max. :91.00 Max. :189.0
##
## roke cevelj lasje oci mati
## Min. :154.0 Min. :36.00 S:19 S:24 Min. :155.0
## 1st Qu.:163.2 1st Qu.:38.00 T:24 T:19 1st Qu.:160.0
## Median :167.8 Median :39.00 Median :165.0
## Mean :169.3 Mean :40.02 Mean :165.4
## 3rd Qu.:172.5 3rd Qu.:41.50 3rd Qu.:168.0
## Max. :193.0 Max. :48.00 Max. :180.0
## NA's :5 NA's :5
## oce majica
## Min. :170.0 L : 5
## 1st Qu.:174.2 M :19
## Median :179.5 S :16
## Mean :179.1 XL: 1
## 3rd Qu.:182.0 XS: 2
## Max. :190.0
## NA's :5Struktura podatkov
str(data)## 'data.frame': 43 obs. of 12 variables:
## $ starost: int 59 21 21 21 21 21 21 20 22 23 ...
## $ mesec : int 7 1 7 8 4 3 7 11 6 10 ...
## $ spol : Factor w/ 2 levels "F","M": 2 1 1 1 1 2 1 1 1 1 ...
## $ masa : int 91 60 55 70 65 88 52 53 62 59 ...
## $ visina : int 178 173 178 167 171 171 162 161 168 169 ...
## $ roke : num 189 176 178 165 168 173 164 160 164 168 ...
## $ cevelj : int 44 43 39 39 40 41 39 38 41 38 ...
## $ lasje : Factor w/ 2 levels "S","T": 2 2 2 1 2 2 2 2 2 1 ...
## $ oci : Factor w/ 2 levels "S","T": 1 2 2 2 1 2 2 2 1 1 ...
## $ mati : int 155 162 170 160 169 165 160 158 170 178 ...
## $ oce : int 180 184 180 190 176 182 170 180 185 180 ...
## $ majica : Factor w/ 5 levels "L","M","S","XL",..: 1 3 3 3 2 4 3 3 2 2 ...Vsi podatki
data## starost mesec spol masa visina roke cevelj lasje oci mati oce majica
## 1 59 7 M 91 178 189.0 44 T S 155 180 L
## 2 21 1 F 60 173 176.0 43 T T 162 184 S
## 3 21 7 F 55 178 178.0 39 T T 170 180 S
## 4 21 8 F 70 167 165.0 39 S T 160 190 S
## 5 21 4 F 65 171 168.0 40 T S 169 176 M
## 6 21 3 M 88 171 173.0 41 T T 165 182 XL
## 7 21 7 F 52 162 164.0 39 T T 160 170 S
## 8 20 11 F 53 161 160.0 38 T T 158 180 S
## 9 22 6 F 62 168 164.0 41 T S 170 185 M
## 10 23 10 F 59 169 168.0 38 S S 178 180 M
## 11 21 9 F 65 170 169.0 40 S S NA NA L
## 12 21 7 F 55 164 167.5 37 T T 160 175 S
## 13 20 2 F 51 156 154.0 38 S S 158 182 XS
## 14 23 6 F 56 170 170.0 39 T S 165 173 S
## 15 21 2 F 56 167 166.0 39 S S 160 180 S
## 16 21 10 M 75 185 193.0 45 S S NA NA M
## 17 21 6 F 63 170 165.0 40 T T NA NA M
## 18 21 8 F 57 168 162.0 38 T T 165 173 S
## 19 20 11 F 63 174 171.0 40 S S 168 173 M
## 20 21 5 F 70 173 169.0 39 T T 164 178 M
## 21 21 4 M 72 183 185.0 44 T S 172 187 M
## 22 21 9 F 66 163 164.0 39 S S 168 177 M
## 23 20 11 M 87 189 190.0 45 T S 180 187 L
## 24 20 8 F 54 168 170.0 40 S S 174 180 M
## 25 22 5 F 65 163 159.0 39 S S 160 172 L
## 26 21 3 F 59 164 165.0 36 S S 165 172 M
## 27 21 5 F 61 174 170.0 40 S S 162 189 M
## 28 20 11 F 62 168 163.0 39 S T 168 183 S
## 29 21 7 F 51 159 157.0 37 T S 157 173 XS
## 30 22 2 F 58 173 NA 42 S S NA NA S
## 31 22 7 M 90 180 NA 42 T T NA NA L
## 32 21 8 M 75 180 NA 43 T T 168 174 M
## 33 21 5 F 61 163 160.0 39 S S 157 173 M
## 34 22 7 F 55 170 NA 39 T T 165 178 S
## 35 23 8 F 59 168 164.0 38 T T 174 188 S
## 36 20 11 M 70 180 181.0 40 S S 166 188 M
## 37 21 11 F 51 166 160.0 38 S S 163 182 S
## 38 22 10 M 73 173 180.0 42 T S 168 175 M
## 39 21 10 F 58 170 171.0 48 S S 177 180 M
## 40 22 7 F 56 158 156.0 37 T T 165 179 M
## 41 21 4 F 55 157 NA 37 T T 157 178 S
## 42 22 10 F 50 160 160.0 37 S T 164 174 S
## 43 22 0 M 73 181 187.0 43 T T 167 175 MPrikaz podatkov
plot(data$starost)
Ali pa:
plot(data[ , 1 ])
plot(data[,"starost"])
!!! zdi se, da je eden ful star!!!
Kaj pa masa?
plot(data$masa)
Izbiranje vrstic in stolpcev
Začasno shranimo podatke še po d drugim imenom
D <- dataD[ , 1 ] # prvi stolpec## [1] 59 21 21 21 21 21 21 20 22 23 21 21 20 23 21 21 21 21 20 21 21 21 20
## [24] 20 22 21 21 20 21 22 22 21 21 22 23 20 21 22 21 22 21 22 22D[1 , ] # prva vrstica## starost mesec spol masa visina roke cevelj lasje oci mati oce majica
## 1 59 7 M 91 178 189 44 T S 155 180 LD[c(1,3,5), c(4,7,9)]## masa cevelj oci
## 1 91 44 S
## 3 55 39 T
## 5 65 40 Sdata$starost<30## [1] FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [12] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [23] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
## [34] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUEfilter <- data$starost<30data[ filter,]## starost mesec spol masa visina roke cevelj lasje oci mati oce majica
## 2 21 1 F 60 173 176.0 43 T T 162 184 S
## 3 21 7 F 55 178 178.0 39 T T 170 180 S
## 4 21 8 F 70 167 165.0 39 S T 160 190 S
## 5 21 4 F 65 171 168.0 40 T S 169 176 M
## 6 21 3 M 88 171 173.0 41 T T 165 182 XL
## 7 21 7 F 52 162 164.0 39 T T 160 170 S
## 8 20 11 F 53 161 160.0 38 T T 158 180 S
## 9 22 6 F 62 168 164.0 41 T S 170 185 M
## 10 23 10 F 59 169 168.0 38 S S 178 180 M
## 11 21 9 F 65 170 169.0 40 S S NA NA L
## 12 21 7 F 55 164 167.5 37 T T 160 175 S
## 13 20 2 F 51 156 154.0 38 S S 158 182 XS
## 14 23 6 F 56 170 170.0 39 T S 165 173 S
## 15 21 2 F 56 167 166.0 39 S S 160 180 S
## 16 21 10 M 75 185 193.0 45 S S NA NA M
## 17 21 6 F 63 170 165.0 40 T T NA NA M
## 18 21 8 F 57 168 162.0 38 T T 165 173 S
## 19 20 11 F 63 174 171.0 40 S S 168 173 M
## 20 21 5 F 70 173 169.0 39 T T 164 178 M
## 21 21 4 M 72 183 185.0 44 T S 172 187 M
## 22 21 9 F 66 163 164.0 39 S S 168 177 M
## 23 20 11 M 87 189 190.0 45 T S 180 187 L
## 24 20 8 F 54 168 170.0 40 S S 174 180 M
## 25 22 5 F 65 163 159.0 39 S S 160 172 L
## 26 21 3 F 59 164 165.0 36 S S 165 172 M
## 27 21 5 F 61 174 170.0 40 S S 162 189 M
## 28 20 11 F 62 168 163.0 39 S T 168 183 S
## 29 21 7 F 51 159 157.0 37 T S 157 173 XS
## 30 22 2 F 58 173 NA 42 S S NA NA S
## 31 22 7 M 90 180 NA 42 T T NA NA L
## 32 21 8 M 75 180 NA 43 T T 168 174 M
## 33 21 5 F 61 163 160.0 39 S S 157 173 M
## 34 22 7 F 55 170 NA 39 T T 165 178 S
## 35 23 8 F 59 168 164.0 38 T T 174 188 S
## 36 20 11 M 70 180 181.0 40 S S 166 188 M
## 37 21 11 F 51 166 160.0 38 S S 163 182 S
## 38 22 10 M 73 173 180.0 42 T S 168 175 M
## 39 21 10 F 58 170 171.0 48 S S 177 180 M
## 40 22 7 F 56 158 156.0 37 T T 165 179 M
## 41 21 4 F 55 157 NA 37 T T 157 178 S
## 42 22 10 F 50 160 160.0 37 S T 164 174 S
## 43 22 0 M 73 181 187.0 43 T T 167 175 Mdata[ !filter,]## starost mesec spol masa visina roke cevelj lasje oci mati oce majica
## 1 59 7 M 91 178 189 44 T S 155 180 LPodatki o masi za tiste, ki so vecji od 165 cm?
filter <- data$visina>165
filter## [1] TRUE TRUE TRUE TRUE TRUE TRUE FALSE FALSE TRUE TRUE TRUE
## [12] FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE
## [23] TRUE TRUE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE
## [34] TRUE TRUE TRUE TRUE TRUE TRUE FALSE FALSE FALSE TRUEVektor mas za “ta velike”
veliki <- data[ filter, "masa"]
veliki## [1] 91 60 55 70 65 88 62 59 65 56 56 75 63 57 63 70 72 87 54 61 62 58 90
## [24] 75 55 59 70 51 73 58 7310:13
lengtttth(10:13)Koliko je velikih?
n <- length( data[ data$visina>165,"masa"])
n## [1] 31length(veliki)## [1] 31Med podatki imamo 31 velikih.
Negativni indeks odstrani element
x <- c(10,3,7,5,4)
x[1]## [1] 10x[-1]## [1] 3 7 5 4