在 R 中选择 data.frame 的前4行

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
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使用索引:

df[1:4,]

括号中的值可以解释为逻辑、数字或字符(匹配各自的名称) :

df[row.index, column.index]

阅读帮助(‘[’)了解关于这个主题的更多细节，也阅读关于 指数矩阵指数矩阵的介绍 R。

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最佳答案

使用 head:

dnow <- data.frame(x=rnorm(100), y=runif(100))
head(dnow,4) ## default is 6
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因为在 DataFrame 上，人们可以简单地键入

head(data, num=10L)

比如说前10个。

对于 data.frame，只需输入

head(data, 10)

拿到前10个。

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如果少于4行，您可以使用 head函数(head(data, 4)或 head(data, n=4)) ，它的工作原理就像魔法一样。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

假设您想选择前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，看看会发生什么情况——您将丢失值

> 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>

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！

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如果有人对 dplyr解决方案感兴趣，它是非常直观的:

dt <- dt %>%
slice(1:4)
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使用 dplyr中的 slice_head的另一个选项:

library(dplyr)
mtcars %>%
slice_head(n = 4)
#>                 mpg cyl disp  hp drat    wt  qsec vs am gear carb
#> Mazda RX4      21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
#> Mazda RX4 Wag  21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
#> Datsun 710     22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
#> Hornet 4 Drive 21.4   6  258 110 3.08 3.215 19.44  1  0    3    1

创建于2022-08-27与 Reprex v2.0.2

请注意: n必须显式命名！


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