2017-12-17
1.选择与查看数据
#选定数据
>data(iris)
#查看数据,按列展开，观测数据类型
>str(iris)
'data.frame': 150 obs. of 5 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#按列展开，进行数据统计观测
>summary(iris)
Sepal.Length Sepal.Width
Min. :4.300 Min. :2.000
1st Qu.:5.100 1st Qu.:2.800
Median :5.800 Median :3.000
Mean :5.843 Mean :3.057
3rd Qu.:6.400 3rd Qu.:3.300
Max. :7.900 Max. :4.400
Petal.Length Petal.Width
Min. :1.000 Min. :0.100
1st Qu.:1.600 1st Qu.:0.300
Median :4.350 Median :1.300
Mean :3.758 Mean :1.199
3rd Qu.:5.100 3rd Qu.:1.800
Max. :6.900 Max. :2.500
Species
setosa :50
versicolor:50
virginica :50
#按行展开，查看前10行
>head(iris,10) Sepal.Length Sepal.Width Petal.Length
1 5.1 3.5 1.4
2 4.9 3.0 1.4
3 4.7 3.2 1.3
4 4.6 3.1 1.5
5 5.0 3.6 1.4
6 5.4 3.9 1.7
7 4.6 3.4 1.4
8 5.0 3.4 1.5
9 4.4 2.9 1.4
10 4.9 3.1 1.5
Petal.Width Species
1 0.2 setosa
2 0.2 setosa
3 0.2 setosa
4 0.2 setosa
5 0.2 setosa
6 0.4 setosa
7 0.3 setosa
8 0.2 setosa
9 0.2 setosa
10 0.1 setosa
#按行展开，观测后10行
>tail(iris,10)
Sepal.Length Sepal.Width Petal.Length
141 6.7 3.1 5.6
142 6.9 3.1 5.1
143 5.8 2.7 5.1
144 6.8 3.2 5.9
145 6.7 3.3 5.7
146 6.7 3.0 5.2
147 6.3 2.5 5.0
148 6.5 3.0 5.2
149 6.2 3.4 5.4
150 5.9 3.0 5.1
Petal.Width Species
141 2.4 virginica
142 2.3 virginica
143 1.9 virginica
144 2.3 virginica
145 2.5 virginica
146 2.3 virginica
147 1.9 virginica
148 2.0 virginica
149 2.3 virginica
150 1.8 virginica
#观测数据内的某一行 `
>table(iris$Sepal.Length)
4.3 4.4 4.5 4.6 4.7 4.8 4.9 5 5.1 5.2
1 3 1 4 2 5 6 10 9 4
5.3 5.4 5.5 5.6 5.7 5.8 5.9 6 6.1 6.2
1 6 7 6 8 7 3 6 6 4
6.3 6.4 6.5 6.6 6.7 6.8 6.9 7 7.1 7.2
9 7 5 2 8 3 4 1 1 3
7.3 7.4 7.6 7.7 7.9
1 1 1 4 1
#观测数据的容量
> object.size(iris)
7088 bytes
深入观测方法
#选择某一行某一列数据,一行一列
>iris[1,1]
[1] 5.1
#使用c()选择多行
> sepal.iris = iris[,c("Sepal.Length","Sepal.Width")]
> str(sepal.iris)
'data.frame': 150 obs. of 2 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#指定观测那几行的那几个
> FIVE.sepal.iris = iris[1:5,c("Sepal.Length","Sepal.Width")]
> str(FIVE.sepal.iris)
'data.frame': 5 obs. of 2 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6
#设置筛选条件，例如iris中species的仅包括setosa类型的数据，后面指定了列数
> setosa.data = iris[iris$Species=="setosa",1:5]
> str(setosa.data)
'data.frame': 50 obs. of 5 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#使用subset函数来获取数据集的子集
> sepal.data = subset(iris,select = c("Sepal.Length","Sepal.Width"))
> str(sepal.data)
'data.frame': 150 obs. of 2 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#subset获取仅包含setosa的数据
> setosa.data = subset(iris,Species=="setosa")
> str(setosa.data)
'data.frame': 50 obs. of 5 variables:
$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#subset运用条件来筛选数据
> example.data = subset(iris,Petal.Length<=1.4 & Petal.Width>=0.2,select = Species )
> str(example.data)
'data.frame': 21 obs. of 1 variable:
$ Species: Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
#具有相同行相同列的数据合并为一组，
> flower.type = data.frame(Species = "setosa",Flower = "iris")
> merge(flower.type,iris[1:3,],by = "Species")
Species Flower Sepal.Length Sepal.Width Petal.Length Petal.Width
1 setosa iris 5.1 3.5 1.4 0.2
2 setosa iris 4.9 3.0 1.4 0.2
3 setosa iris 4.7 3.2 1.3 0.2
#函数order可以返回指定列进行数据排序后的数据框，下面是花萼长度从大到小排序
> head(iris[order(iris$Sepal.Length,decreasing = TRUE),])
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
132 7.9 3.8 6.4 2.0 virginica
118 7.7 3.8 6.7 2.2 virginica
119 7.7 2.6 6.9 2.3 virginica
123 7.7 2.8 6.7 2.0 virginica
136 7.7 3.0 6.1 2.3 virginica
106 7.6 3.0 6.6 2.1 virginica
扩展
#函数sub与gsub支持使用正则表达示对字符串的处理，分别替换第一个字符与所有字符
> iris10 = iris
> sub("e","z",names(iris10))
[1] "Szpal.Length" "Szpal.Width" "Pztal.Length" "Pztal.Width" "Spzcies"
> gsub("e","z",names(iris10))
[1] "Szpal.Lzngth" "Szpal.Width" "Pztal.Lzngth" "Pztal.Width" "Spzcizs"
完 谢谢观看
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