data1 <- data.frame(Titanic)
str(data1)
## 'data.frame':    32 obs. of  5 variables:
##  $ Class   : Factor w/ 4 levels "1st","2nd","3rd",..: 1 2 3 4 1 2 3 4 1 2 ...
##  $ Sex     : Factor w/ 2 levels "Male","Female": 1 1 1 1 2 2 2 2 1 1 ...
##  $ Age     : Factor w/ 2 levels "Child","Adult": 1 1 1 1 1 1 1 1 2 2 ...
##  $ Survived: Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
##  $ Freq    : num  0 0 35 0 0 0 17 0 118 154 ...
summary(data1)
##   Class       Sex        Age     Survived      Freq       
##  1st :8   Male  :16   Child:16   No :16   Min.   :  0.00  
##  2nd :8   Female:16   Adult:16   Yes:16   1st Qu.:  0.75  
##  3rd :8                                   Median : 13.50  
##  Crew:8                                   Mean   : 68.78  
##                                           3rd Qu.: 77.00  
##                                           Max.   :670.00
colSums(is.na(data1))
##    Class      Sex      Age Survived     Freq 
##        0        0        0        0        0
data1 <- as.data.frame(datasets::Titanic)
str(data1)
## 'data.frame':    32 obs. of  5 variables:
##  $ Class   : Factor w/ 4 levels "1st","2nd","3rd",..: 1 2 3 4 1 2 3 4 1 2 ...
##  $ Sex     : Factor w/ 2 levels "Male","Female": 1 1 1 1 2 2 2 2 1 1 ...
##  $ Age     : Factor w/ 2 levels "Child","Adult": 1 1 1 1 1 1 1 1 2 2 ...
##  $ Survived: Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
##  $ Freq    : num  0 0 35 0 0 0 17 0 118 154 ...
print(data1)
##    Class    Sex   Age Survived Freq
## 1    1st   Male Child       No    0
## 2    2nd   Male Child       No    0
## 3    3rd   Male Child       No   35
## 4   Crew   Male Child       No    0
## 5    1st Female Child       No    0
## 6    2nd Female Child       No    0
## 7    3rd Female Child       No   17
## 8   Crew Female Child       No    0
## 9    1st   Male Adult       No  118
## 10   2nd   Male Adult       No  154
## 11   3rd   Male Adult       No  387
## 12  Crew   Male Adult       No  670
## 13   1st Female Adult       No    4
## 14   2nd Female Adult       No   13
## 15   3rd Female Adult       No   89
## 16  Crew Female Adult       No    3
## 17   1st   Male Child      Yes    5
## 18   2nd   Male Child      Yes   11
## 19   3rd   Male Child      Yes   13
## 20  Crew   Male Child      Yes    0
## 21   1st Female Child      Yes    1
## 22   2nd Female Child      Yes   13
## 23   3rd Female Child      Yes   14
## 24  Crew Female Child      Yes    0
## 25   1st   Male Adult      Yes   57
## 26   2nd   Male Adult      Yes   14
## 27   3rd   Male Adult      Yes   75
## 28  Crew   Male Adult      Yes  192
## 29   1st Female Adult      Yes  140
## 30   2nd Female Adult      Yes   80
## 31   3rd Female Adult      Yes   76
## 32  Crew Female Adult      Yes   20
sort(data1$Freq)
##  [1]   0   0   0   0   0   0   0   0   1   3   4   5  11  13  13  13  14  14  17
## [20]  20  35  57  75  76  80  89 118 140 154 192 387 670
boxplot.stats(data1$Freq)$out
## [1] 387 670
length(boxplot.stats(data1$Freq)$out)
## [1] 2
data1 <- as.data.frame(datasets::Titanic)
sum(duplicated(data1))
## [1] 0