Q:

What does the replace mean in sample function?

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.
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.
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)

A:

Let's first understand the concept of replace.
By default replace is FALSE in sample. So when you do 
sample(1:5, 2)
#[1] 4 1

As replace is default set to FALSE you are not allowed to repeat elements.  It will randomly select 2 unique elements from 1:5.
But now when you do
sample(1:5, 6)

it results in an error stating

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

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

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. 

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), ])

This will be TRUE only when the number of rows in the dataframe is less than 10. 
Using reproducible example from mtcars
table(mtcars$cyl)

# 4  6  8 
#11  7 14 

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

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

