Question

如何选择data.frame的前4行：

              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

Answer 1

使用head：

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

Answer 2

使用索引：

df[1:4,]

括号中的值可以解释为逻辑，数字或字符（匹配相应的名称）：

df[row.index, column.index]

阅读帮助（`[`）以获取有关此主题的更多详细信息，并阅读R简介中的index matrices。

Answer 3

如果您的行数少于4行，则可以使用head函数（head(data, 4)或head(data, n=4)），它就像魅力一样。但是，假设我们有以下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

让我们说，您想要选择前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，让我们假设您尝试检索前19行，看看会发生什么 - 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

希望这有帮助！

Answer 4

如果有人对dplyr解决方案感兴趣，那么它非常直观：

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

Answer 5

对于DataFrame，只需键入

即可

head(data, num=10L)

获得前10个例子。

对于data.frame，只需键入

即可

head(data, 10)

获得第10名。

在R中选择data.frame的前4行

5 个答案: