示例函数中的替换是什么意思? [英] What does the replace mean in sample function?

问题描述

当我尝试从数据框中随机选择每组中的 10 个样本时，我试图弄清楚样本函数是如何工作的.

I try to figure out how dose the sample function work when I try to random select 10 samples in each group from the data frame.

我有一个包含 5 列和 7000 行的数据框.我将数据集分成大约 200 组.然后我想从每组中随机选择 10 个样本.有些组的样本少于 10 个.因此，当我尝试对它们进行采样时，我设置了 replace=T.然而，当我检查输出时，我发现一些组中有超过 10 个样本的组有重复样本.

I have a data frame with 5 columns and 7000 rows. I split the dataset into around 200 groups. Then I want to random select 10 samples from each group. Some groups have less 10 samples. So when I try to sample them, I set replace=T. However, when I check the output, I found out some groups which were more then 10 sample in the group have repeat samples.

我不知道如何解决这个问题?

I am not sure how to fix this?

  mydata2<- split(mydf,mydf$Group)
  names(mydata2)<-paste0("mydata2",1:length(levels(mydf$Group))) 
  mysample<-Map(function(x) x[sample((1:nrow(x)),size=10,replace=T),], 
  mydata2)

推荐答案

先来了解一下replace的概念.

默认情况下，replace 在 sample 中是 FALSE.所以当你做

By default replace is FALSE in sample. So when you do

sample(1:5, 2)
#[1] 4 1

因为 replace 默认设置为 FALSE，所以不允许重复元素.它将从 1:5 中随机选择 2 个 unique 元素.

As replace is default set to FALSE you are not allowed to repeat elements. It will randomly select 2 unique elements from 1:5.

但是现在当你这样做

sample(1:5, 6)

它导致错误说明

sample.int(length(x), size, replace, prob) 中的错误:'replace = FALSE' 时不能取大于总体的样本

Error in sample.int(length(x), size, replace, prob) : cannot take a sample larger than the population when 'replace = FALSE'

这意味着您正在尝试从 1:5 中提取 6 个 唯一 元素，这是不可能的，因为其中只有 5 个唯一元素.因此，当您设置 replace = TRUE 时，您表示允许重复元素.

which means you are trying to take 6 unique element from 1:5 which is not possible because you have only 5 unique elements in them. So when you set replace = TRUE you say that elements are allowed to be repeated.

sample(1:5, 6, replace = TRUE)
#[1] 3 3 5 3 1 1

在这里，我们看到 replace = TRUE 元素 3 被重复，而在第一个示例中，你运行它多少次，它永远不会重复元素.

Here, we see with replace = TRUE element 3 is repeated whereas in first example how many times you run it, it will never repeat elements.

那么现在，我希望 replace 的概念对你来说是清楚的.现在您只想在列表中少于 10 行时重复行.所以你可以相应地添加一个条件，

So now, I hope the concept of replace is clear to you. Now you want to repeat rows only when there are less than 10 rows in the list. So you can add a condition accordingly,

lapply(mydata2, function(x) x[sample(1:nrow(x) ,size=10, replace=nrow(x) < 10), ])

仅当数据帧中的行数小于 10 时，这将是 TRUE.

This will be TRUE only when the number of rows in the dataframe is less than 10.

使用来自 mtcars

table(mtcars$cyl)

# 4  6  8 
#11  7 14 

我们看到 cyl = 6 有 7 行，小于 10.

We see cyl = 6 has 7 rows which is less than 10.

mydata2 <- split(mtcars, mtcars$cyl)

lapply(mydata2, function(x) x[sample(1:nrow(x) ,size=10, replace=nrow(x) < 10), ])


#$`4`
#                mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#Fiat X1-9      27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
#Merc 230       22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
#Toyota Corolla 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
#Honda Civic    30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
#Toyota Corona  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
#Lotus Europa   30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
#Volvo 142E     21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
#Fiat 128       32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
#Datsun 710     22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#Merc 240D      24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2

#$`6`
#                mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#Valiant        18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#Valiant.1      18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#Mazda RX4      21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#Ferrari Dino   19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
#Valiant.2      18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
#Mazda RX4.1    21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#Mazda RX4 Wag  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
#Merc 280C      17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
#Hornet 4 Drive 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#Merc 280       19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4

#$`8`
#                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
#Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
#Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
#Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
#AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
#Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
#Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
#Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
#Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4

在输出中，我们可以看到仅对 cyl = 6 重复的行，而不是其他任何人.

In the output we can see the rows are repeated only for cyl = 6 and not for anybody else.

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