學(xué)習(xí)一個(gè)R包
安裝R包
如果要安裝的R包在CRAN網(wǎng)站，那么輸入install.packages(“包”), 如果R包在Bioconductor，那么輸入BiocManager::install(“包”)。
dplyr的運(yùn)用
image.png
按照示例數(shù)據(jù)加載測試數(shù)據(jù)之后，本想看一看test數(shù)據(jù)的樣子，發(fā)現(xiàn)除了點(diǎn)bug，view的v要大寫才可以。
1、mutate():新增列
mutate(test, new = Petal.Length*Petal.Width)
image.png
2、select()：按列篩選
> select(test,2)
Sepal.Width
1 3.5
2 3.0
51 3.2
52 3.2
101 3.3
102 2.7
> select(test,c(1,4))
Sepal.Length Petal.Width
1 5.1 0.2
2 4.9 0.2
51 7.0 1.4
52 6.4 1.5
101 6.3 2.5
102 5.8 1.9
> select(test, Sepal.Length, Petal.Width)
Sepal.Length Petal.Width
1 5.1 0.2
2 4.9 0.2
51 7.0 1.4
52 6.4 1.5
101 6.3 2.5
102 5.8 1.9
> select(test, one_of(c("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
3、filter()：按行篩選
> filter(test, Sepal.Width ==3.2)
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.Width ==3.2 & Petal.Length>4.5)
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1 7 3.2 4.7 1.4 versicolor
> filter(test, Species %in% c("setosa","virginica"))
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 6.3 3.3 6.0 2.5 virginica
4 5.8 2.7 5.1 1.9 virginica
4、arrange()：自定義排序
> arrange(test, Petal.Length)#默認(rèn)從小到大排序
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()
> arrange(test, desc(Petal.Length))#用desc從大到小
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
5、summarise()：匯總
> ?summarise()
> summarise(test, first(Sepal.Length), max(Sepal.Length))# Sepal.Length的平第一個(gè)和最大值
first(Sepal.Length) max(Sepal.Length)
1 5.1 7
> 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))
`summarise()` ungrouping output (override with `.groups` argument)
# 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
6、管道操作：相當(dāng)于走了捷徑
> test %>%
+ group_by(Species) %>%
+ summarise(mean(Sepal.Length), sd(Sepal.Length))
`summarise()` ungrouping output (override with `.groups` argument)
# 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
7、count統(tǒng)計(jì)unique值
> count(test,Species)
Species n
1 setosa 2
2 versicolor 2
3 virginica 2
今天暫時(shí)到這
