选择R中data.frame的前4行

如何选择a的前4行data.frame：

              Weight Response
1   Control     59      0.0
2 Treatment     90      0.8
3 Treatment     47      0.1
4 Treamment    106      0.1
5   Control     85      0.7
6 Treatment     73      0.6
7   Control     61      0.2

用途head：

dnow <- data.frame(x=rnorm(100), y=runif(100))
head(dnow,4) ## default is 6

使用索引：

df[1:4,]

括号中的值可以解释为逻辑，数字或字符（与相应的名称匹配）：

df[row.index, column.index]

阅读help（`[`）以获得有关此主题的更多详细信息，并在R简介中阅读有关索引矩阵的信息。

如果有人对dplyr解决方案感兴趣，这非常直观：

dt <- dt %>%
  slice(1:4)

如果少于4行，则可以使用head函数（head(data, 4)或head(data, n=4)），它的作用就像一个超级按钮。但是，假设我们有以下具有15行的数据集

>data <- data <- read.csv("./data.csv", sep = ";", header=TRUE)

>data
 LungCap Age Height Smoke Gender Caesarean
1    6.475   6   62.1    no   male        no
2   10.125  18   74.7   yes female        no
3    9.550  16   69.7    no female       yes
4   11.125  14   71.0    no   male        no
5    4.800   5   56.9    no   male        no
6    6.225  11   58.7    no female        no
7    4.950   8   63.3    no   male       yes
8    7.325  11   70.4    no  male         no
9    8.875  15   70.5    no   male        no
10   6.800  11   59.2    no   male        no
11   6.900  12   59.3    no   male        no
12   6.100  13   59.4    no   male        no
13   6.110  14   59.5    no   male        no
14   6.120  15   59.6    no   male        no
15   6.130  16   59.7    no   male        no

假设您要选择前10行。最简单的方法是data[1:10, ]。

> data[1:10,]
   LungCap Age Height Smoke Gender Caesarean
1    6.475   6   62.1    no   male        no
2   10.125  18   74.7   yes female        no
3    9.550  16   69.7    no female       yes
4   11.125  14   71.0    no   male        no
5    4.800   5   56.9    no   male        no
6    6.225  11   58.7    no female        no
7    4.950   8   63.3    no   male       yes
8    7.325  11   70.4    no  male         no
9    8.875  15   70.5    no   male        no
10   6.800  11   59.2    no   male        no

但是，假设您尝试检索前19行并查看会发生什么-您将缺少值

> data[1:19,]
     LungCap Age Height Smoke Gender Caesarean
1      6.475   6   62.1    no   male        no
2     10.125  18   74.7   yes female        no
3      9.550  16   69.7    no female       yes
4     11.125  14   71.0    no   male        no
5      4.800   5   56.9    no   male        no
6      6.225  11   58.7    no female        no
7      4.950   8   63.3    no   male       yes
8      7.325  11   70.4    no  male         no
9      8.875  15   70.5    no   male        no
10     6.800  11   59.2    no   male        no
11     6.900  12   59.3    no   male        no
12     6.100  13   59.4    no   male        no
13     6.110  14   59.5    no   male        no
14     6.120  15   59.6    no   male        no
15     6.130  16   59.7    no   male        no
NA        NA  NA     NA  <NA>   <NA>      <NA>
NA.1      NA  NA     NA  <NA>   <NA>      <NA>
NA.2      NA  NA     NA  <NA>   <NA>      <NA>
NA.3      NA  NA     NA  <NA>   <NA>      <NA>

并使用head（）函数，

> head(data, 19) # or head(data, n=19)
   LungCap Age Height Smoke Gender Caesarean
1    6.475   6   62.1    no   male        no
2   10.125  18   74.7   yes female        no
3    9.550  16   69.7    no female       yes
4   11.125  14   71.0    no   male        no
5    4.800   5   56.9    no   male        no
6    6.225  11   58.7    no female        no
7    4.950   8   63.3    no   male       yes
8    7.325  11   70.4    no  male         no
9    8.875  15   70.5    no   male        no
10   6.800  11   59.2    no   male        no
11   6.900  12   59.3    no   male        no
12   6.100  13   59.4    no   male        no
13   6.110  14   59.5    no   male        no
14   6.120  15   59.6    no   male        no
15   6.130  16   59.7    no   male        no

希望有帮助！

对于在DataFrame中，您只需键入

head(data, num=10L)

例如获得前10个。

对于data.frame，只需键入

head(data, 10)

得到第一个10。