Tutoial5-week
HangGu
2021/11/28
#Exploring Data with R
#It is very important to explore data before starting to build a predictive model. It gives an idea about the structure of the dataset like number of #continuous or categorical variables and number of observations (rows).
#Choose the dataset “attitude” from the R Datasets Package.
#Prepare an R Markdown document for this lab work.
#Determine what R function to use for the following:
#1.See basic descriptive statistics
summary(attitude)## rating complaints privileges learning raises
## Min. :40.00 Min. :37.0 Min. :30.00 Min. :34.00 Min. :43.00
## 1st Qu.:58.75 1st Qu.:58.5 1st Qu.:45.00 1st Qu.:47.00 1st Qu.:58.25
## Median :65.50 Median :65.0 Median :51.50 Median :56.50 Median :63.50
## Mean :64.63 Mean :66.6 Mean :53.13 Mean :56.37 Mean :64.63
## 3rd Qu.:71.75 3rd Qu.:77.0 3rd Qu.:62.50 3rd Qu.:66.75 3rd Qu.:71.00
## Max. :85.00 Max. :90.0 Max. :83.00 Max. :75.00 Max. :88.00
## critical advance
## Min. :49.00 Min. :25.00
## 1st Qu.:69.25 1st Qu.:35.00
## Median :77.50 Median :41.00
## Mean :74.77 Mean :42.93
## 3rd Qu.:80.00 3rd Qu.:47.75
## Max. :92.00 Max. :72.00#a)What is the difference between (attitude[3]) and (attitude$learning)
attitude[3]## privileges
## 1 30
## 2 51
## 3 68
## 4 45
## 5 56
## 6 49
## 7 42
## 8 50
## 9 72
## 10 45
## 11 53
## 12 47
## 13 57
## 14 83
## 15 54
## 16 50
## 17 64
## 18 65
## 19 46
## 20 68
## 21 33
## 22 52
## 23 52
## 24 42
## 25 42
## 26 66
## 27 58
## 28 44
## 29 71
## 30 39attitude$learning## [1] 39 54 69 47 66 44 56 55 67 47 58 39 42 45 72 72 69 75 57 54 34 62 50 58 48
## [26] 63 74 45 71 59#2.Lists name of variables in a dataset
names(attitude)## [1] "rating" "complaints" "privileges" "learning" "raises"
## [6] "critical" "advance"#3.Calculate number of rows in a dataset
dim(attitude)[1]## [1] 30#4.Calculate number of columns in a dataset
dim(attitude)[2]## [1] 7#5.List structure of a dataset
str(attitude)## 'data.frame': 30 obs. of 7 variables:
## $ rating : num 43 63 71 61 81 43 58 71 72 67 ...
## $ complaints: num 51 64 70 63 78 55 67 75 82 61 ...
## $ privileges: num 30 51 68 45 56 49 42 50 72 45 ...
## $ learning : num 39 54 69 47 66 44 56 55 67 47 ...
## $ raises : num 61 63 76 54 71 54 66 70 71 62 ...
## $ critical : num 92 73 86 84 83 49 68 66 83 80 ...
## $ advance : num 45 47 48 35 47 34 35 41 31 41 ...#6.See first 6 rows (by default) of dataset
head(attitude)## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34#7.See first n rows of dataset
#Select to see the first 15 rows of dataset
head(attitude,n=15)## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46#8.See all rows but the last row
head(attitude,n=-1)## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46
## 16 81 90 50 72 60 54 36
## 17 74 85 64 69 79 79 63
## 18 65 60 65 75 55 80 60
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55#9.See last 6 rows (by default) of a dataset
tail(attitude)## rating complaints privileges learning raises critical advance
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39#10.See last n rows of dataset
#Select to see the last 12 rows of dataset.
tail(attitude,n=12)## rating complaints privileges learning raises critical advance
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39#11.See the last n rows but the first row
tail(attitude,n=-1)## rating complaints privileges learning raises critical advance
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46
## 16 81 90 50 72 60 54 36
## 17 74 85 64 69 79 79 63
## 18 65 60 65 75 55 80 60
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39#12.Number of missing values
#Which function will returns number of missing values in each variable of a dataset?
sapply(attitude,function(attitude) sum(is.na(attitude)))## rating complaints privileges learning raises critical advance
## 0 0 0 0 0 0 0#13.Number of missing values in a single variable
sum(is.na(attitude$rating))## [1] 0#14.Plot a simple graph, which will appear on a screen device.
plot(attitude)
#15.Plot the graph shown below, and make it appear on a file device (a pdf file)
with(attitude,(plot(privileges,learning,main="Learning Attitude",xlab="Privileges",ylab="Learning")))
## NULLR Markdown
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.
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summary(cars)## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
## Max. :25.0 Max. :120.00Including Plots
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