DAY6-。
2020-01-19 本文已影响0人
911c66788b0c
R包安装命令
>install.packages(“包”) >或者BiocManager::install（“包”）
（<u>取决于包存在于SCAN还是Biocductor</u>）
R包的加载
>library(包)
>require(包)
示例：dplyr包的加载
> library(dplyr)
载入程辑包：‘dplyr’
The following objects are masked from ‘package:stats’:
filter, lag
The following objects are masked from ‘package:base’:
intersect, setdiff, setequal, union
Warning message:
程辑包‘dplyr’是用R版本3.6.2 来建造的
>
test
test
mutate #新增列
select #选择列（可以按<u>列号</u>也可以按<u>列名</u>筛选）
filter #选择行
arrange #按某1列或某几列对整个表格进行排序
summarise #汇总
> mutate(test, new = Sepal.Length * Sepal.Width)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species new
1 5.1 3.5 1.4 0.2 setosa 17.85
2 4.9 3.0 1.4 0.2 setosa 14.70
3 7.0 3.2 4.7 1.4 versicolor 22.40
4 6.4 3.2 4.5 1.5 versicolor 20.48
5 6.3 3.3 6.0 2.5 virginica 20.79
6 5.8 2.7 5.1 1.9 virginica 15.66
> select(test,1)
Sepal.Length
1 5.1
2 4.9
51 7.0
52 6.4
101 6.3
102 5.8
> select(test,c(1,3))
Sepal.Length Petal.Length
1 5.1 1.4
2 4.9 1.4
51 7.0 4.7
52 6.4 4.5
101 6.3 6.0
102 5.8 5.1
> select(test,c(1,5))
Sepal.Length Species
1 5.1 setosa
2 4.9 setosa
51 7.0 versicolor
52 6.4 versicolor
101 6.3 virginica
102 5.8 virginica
> select(test,Sepal.Length)
Sepal.Length
1 5.1
2 4.9
51 7.0
52 6.4
101 6.3
102 5.8
> select(test,Sepal.Width)
Sepal.Width
1 3.5
2 3.0
51 3.2
52 3.2
101 3.3
102 2.7
> select(test, Petal.Length, Petal.Width)
Petal.Length Petal.Width
1 1.4 0.2
2 1.4 0.2
51 4.7 1.4
52 4.5 1.5
101 6.0 2.5
102 5.1 1.9
> filter(test, Species == "setosa")
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
> filter(test, Species == "versicolor")
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 7.0 3.2 4.7 1.4 versicolor
2 6.4 3.2 4.5 1.5 versicolor
> filter(test, Sepal.Length > 5)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 7.0 3.2 4.7 1.4 versicolor
3 6.4 3.2 4.5 1.5 versicolor
4 6.3 3.3 6.0 2.5 virginica
5 5.8 2.7 5.1 1.9 virginica
> filter(test, Species == "setosa"&Sepal.Length > 5)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
> filter(test, Species %in% c("setosa","versicolor"))
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 7.0 3.2 4.7 1.4 versicolor
4 6.4 3.2 4.5 1.5 versicolor
> arrange(test, Sepal.Length)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 4.9 3.0 1.4 0.2 setosa
2 5.1 3.5 1.4 0.2 setosa
3 5.8 2.7 5.1 1.9 virginica
4 6.3 3.3 6.0 2.5 virginica
5 6.4 3.2 4.5 1.5 versicolor
6 7.0 3.2 4.7 1.4 versicolor
> arrange(test, desc(Sepal.Length))
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 7.0 3.2 4.7 1.4 versicolor
2 6.4 3.2 4.5 1.5 versicolor
3 6.3 3.3 6.0 2.5 virginica
4 5.8 2.7 5.1 1.9 virginica
5 5.1 3.5 1.4 0.2 setosa
6 4.9 3.0 1.4 0.2 setosa
> arrange(test, Petal.Length)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3.0 1.4 0.2 setosa
3 6.4 3.2 4.5 1.5 versicolor
4 7.0 3.2 4.7 1.4 versicolor
5 5.8 2.7 5.1 1.9 virginica
6 6.3 3.3 6.0 2.5 virginica
> arrange(test, desc(Petal.Length))
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 6.3 3.3 6.0 2.5 virginica
2 5.8 2.7 5.1 1.9 virginica
3 7.0 3.2 4.7 1.4 versicolor
4 6.4 3.2 4.5 1.5 versicolor
5 5.1 3.5 1.4 0.2 setosa
6 4.9 3.0 1.4 0.2 setosa
> summarise(test, mean(Sepal.Length), sd(Sepal.Length))
mean(Sepal.Length) sd(Sepal.Length)
1 5.916667 0.8084965
> summarise(test, mean(Sepal.Length), sd(Sepal.Length))
mean(Sepal.Length) sd(Sepal.Length)
1 5.916667 0.8084965
> group_by(test, Species)
# A tibble: 6 x 5
# Groups: Species [3]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
* <dbl> <dbl> <dbl> <dbl> <fct>
1 5.1 3.5 1.4 0.2 setosa
2 4.9 3 1.4 0.2 setosa
3 7 3.2 4.7 1.4 versicolor
4 6.4 3.2 4.5 1.5 versicolor
5 6.3 3.3 6 2.5 virginica
6 5.8 2.7 5.1 1.9 virginica
> summarise(group_by(test, Species),mean(Sepal.Length), sd(Sepal.Length))
# A tibble: 3 x 3
Species `mean(Sepal.Length)` `sd(Sepal.Length)`
<fct> <dbl> <dbl>
1 setosa 5 0.141
2 versicolor 6.7 0.424
3 virginica 6.05 0.354
> test %>%
+ group_by(Species) %>%
+ summarise(mean(Sepal.Length), sd(Sepal.Length))
# A tibble: 3 x 3
Species `mean(Sepal.Length)` `sd(Sepal.Length)`
<fct> <dbl> <dbl>
1 setosa 5 0.141
2 versicolor 6.7 0.424
3 virginica 6.05 0.354
> count(test,Species)
# A tibble: 3 x 2
Species n
<fct> <int>
1 setosa 2
2 versicolor 2
3 virginica 2
