Select R 中 data.frame 的前 4 行

Question

我怎樣才能 select 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,]

括號中的值可以解釋為邏輯，數字或字符（匹配相應的名稱）：

df[row.index, column.index]

閱讀幫助（`[`）以獲取有關此主題的更多詳細信息，並閱讀R簡介中的索引矩陣 。

Answer 3

如果有人對dplyr解決方案感興趣，它非常直觀：

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

Answer 4

如果你有少於4行，你可以使用head功能（ head(data, 4)或head(data, n=4) ），它就像一個魅力。 但是，假設我們有以下15行的數據集

>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

比方說，你想選擇前10行。 最簡單的方法是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，假設您嘗試檢索前19行並查看發生的情況 - 您將缺少值

> 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>

並使用head（）函數，

> 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

希望這有幫助！

Answer 5

對於DataFrame，可以簡單地輸入

head(data, num=10L)

以前10個為例。

對於data.frame，可以簡單地輸入

head(data, 10)

獲得前10名。

Answer 6

使用dplyr中的slice_head的另一個選項：

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

^{使用reprex v2.0.2創建於 2022-08-27}

請注意： n必須明確命名！