0311.R

#連續資料分析
x <- mtcars
x

##                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
## Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
## Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
## Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
## Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
## Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
## Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
## Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
## Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
## Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
## Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
## Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
## Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
## Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
## Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
## Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
## Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
## Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
## AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
## Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
## Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
## Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
## Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
## Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
## Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
## Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
## Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
## Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

summary(x)

##       mpg             cyl             disp             hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##       drat             wt             qsec             vs        
##  Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
##  1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
##  Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
##  Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
##  3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
##  Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
##        am              gear            carb      
##  Min.   :0.0000   Min.   :3.000   Min.   :1.000  
##  1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
##  Median :0.0000   Median :4.000   Median :2.000  
##  Mean   :0.4062   Mean   :3.688   Mean   :2.812  
##  3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
##  Max.   :1.0000   Max.   :5.000   Max.   :8.000

str(x)

## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

# [, 1] mpg ：Miles/(US) gallon 耗油量
# [, 2] cyl ：Number of cylinders 汽缸數
# [, 3] disp：Displacement (cu.in., cubic inch) 排氣量
# [, 4] hp  ：Gross horsepower 馬力
# [, 5] drat：Rear axle ratio 後輪軸減速比
# [, 6] wt  ：Weight (1000 lbs) 車體重量
# [, 7] qsec：1/4 mile time 1/4英里加速秒數
# [, 8] vs  ：V/S，0代表V型引擎，1代表直立式引擎
# [, 9] am  ：Transmission (0 = automatic自排, 1 = manual手排) 
# [,10] gear：Number of forward gears 變速箱
# [,11] carb：Number of carburetors化油器


#一、變速箱(gear)可分為3速、4速、5速，請計算這三類的佔比為何？並畫圖示之。
g<-table(x$gear)
g

## 
##  3  4  5 
## 15 12  5

p.g<- prop.table(g)
p.g

## 
##       3       4       5 
## 0.46875 0.37500 0.15625

p.g<-p.g*100
barplot(p.g)

pie(p.g)

#二、請計算「馬力」(hp)的1.平均數、2.中位數、3.全距、4.標準差、5.變異數
x$hp

##  [1] 110 110  93 110 175 105 245  62  95 123 123 180 180 180 205 215 230  66  52
## [20]  65  97 150 150 245 175  66  91 113 264 175 335 109

mean(x$hp)#平均數

## [1] 146.6875

median(x$hp)#中位數

## [1] 123

max(x$hp)#最大值

## [1] 335

min(x$hp)#最小值

## [1] 52

max(x$hp)-min(x$hp)

## [1] 283

sd(x$hp)#標準差

## [1] 68.56287

var(x$hp)#變異數

## [1] 4700.867

#三、請繪製「馬力」(hp)的盒狀圖與直方圖
boxplot(x$hp,main="hp",
        sub= "Timmy",col=9)

hist(x$hp,
     main="horsepower",
     sub= "Timmy",
     col=123)#直方圖

#四、手自排(am)可分為(0 = automatic自排, 1 = manual手排) 請計算這三類的佔比為何？並畫圖示之。
x$am

##  [1] 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 1 1 1 1

a<-table(x$am)
a

## 
##  0  1 
## 19 13

p.a<- prop.table(a)
p.a

## 
##       0       1 
## 0.59375 0.40625

p.a<-p.a*100
p.a

## 
##      0      1 
## 59.375 40.625

barplot(p.a)

rownames(p.a)

## [1] "0" "1"

barplot(p.a, 
     
      
        col =c(117,113),
        main="am",
        sub="Timmy")

pie(p.a, col = c(2,4,8),main="am",sub= "Timmy")

#五、請計算wt：Weight車體重量的1.平均數、2.中位數、3.全距、4.標準差、5.變異數、
x$wt

##  [1] 2.620 2.875 2.320 3.215 3.440 3.460 3.570 3.190 3.150 3.440 3.440 4.070
## [13] 3.730 3.780 5.250 5.424 5.345 2.200 1.615 1.835 2.465 3.520 3.435 3.840
## [25] 3.845 1.935 2.140 1.513 3.170 2.770 3.570 2.780

mean(x$wt)#平均數

## [1] 3.21725

median(x$wt)#中位數

## [1] 3.325

max(x$wt)#最大值

## [1] 5.424

min(x$wt)#最小值

## [1] 1.513

max(x$wt)-min(x$wt)

## [1] 3.911

sd(x$wt)#標準差

## [1] 0.9784574

var(x$wt)#變異數

## [1] 0.957379

#六、請繪製wt：Weight車體重量的盒狀圖與直方圖？
hist(x$wt,
     main="Weight",
     sub= "Timmy",
     col=13)#直方圖

boxplot(x$wt,main="Weight",
        sub= "Timmy",col=9)

0311.R

rstudio-user

2021-03-11