## R :Looping through each 5 rows of data frame and imputing incremental value

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This is your data:

df = read.table(text = "state Value a 1 b 2 a 3 c 4 a 5 e 6 f 7 w 8 f 9 s 10 e 11 r 12 s 13 s 14", header=T)

You can now use `rownames`

to help you to impute the incremental values. The line of code below gives you your desired output, by taking the row indices, dividing them by `5`

and then obtaining the `ceiling`

(i.e., the closest greater integer).

df$Increment <- ceiling(as.numeric(rownames(df))/5)

Which will give you your expected output:

# state Value Increment # 1 a 1 1 # 2 b 2 1 # 3 a 3 1 # 4 c 4 1 # 5 a 5 1 # 6 e 6 2 # 7 f 7 2 # 8 w 8 2 # 9 f 9 2 # 10 s 10 2 # 11 e 11 3 # 12 r 12 3 # 13 s 13 3 # 14 s 14 3

Hope it helps.

**21 Iteration,** This is very important for efficiency: if you grow the for loop at each iteration using what to loop over: each run of the for loop will assign i to a different value from 1, 2) output <- double() for (i in seq_along(means)) { n <- sample(100, 1) output Write a function that prints the mean of each numeric column in a data frame, The loop functions in R are very powerful because they allow you to conduct a series of operations on data using a compact form. The operation of a loop function involves iterating over an R object (e.g. a list or vector or matrix), applying a function to each element of the object, and the collating the results and returning the collated results.

Here's a `dplyr`

solution that checks whether the remainder of dividing the row number minus one with 5 is 0. If it is 0 it increases the value of the new column by 1.

dt = read.table(text = "state Value a 1 b 2 a 3 c 4 a 5 e 6 f 7 w 8 f 9 s 10 e 11 r 12 s 13 s 14", header=T) library(dplyr) dt %>% mutate(Increment = cumsum((row_number()-1) %% 5 == 0)) # state Value Increment # 1 a 1 1 # 2 b 2 1 # 3 a 3 1 # 4 c 4 1 # 5 a 5 1 # 6 e 6 2 # 7 f 7 2 # 8 w 8 2 # 9 f 9 2 # 10 s 10 2 # 11 e 11 3 # 12 r 12 3 # 13 s 13 3 # 14 s 14 3

**Loops and Functions in R,** We'll start this lesson with this last idea: How can we have R make decisions for us? How can we go through and update our table? For example, we can do something to every row of our dataframe. Using the names above, each iteration of variable takes the value of one of the elements of vector . [1] 1 2 3 4 5 6. A for loop is very valuable when we need to iterate over a list of elements or a range of numbers. Loop can be used to iterate over a list, data frame, vector, matrix or any other object.

The following function will do what you want. Arguments:

`DF`

- the input data.frame;`N`

- the number of repeats of each value in the increment;`newcol`

- the name of the increment column, defaults to`"Increment"`

.

Just assign the result to the new df.

fun <- function(DF, N, newcol = "Increment"){ n <- nrow(DF) f <- rep_len(c(1, rep(0, N - 1)), length.out = n) DF[[newcol]] <- cumsum(f) DF } fun(df1, N = 5)

**Data.**

set.seed(1234) # Make the results reproducible n <- 14 state <- sample(letters, n, TRUE) Value <- seq_len(n) df1 <- data.frame(state, Value)

**A Tutorial on Loops in R – Usage and Alternatives,** Introduction In this easy-to-follow R tutorial on loops we will examine the we assign initial values to a control loop variable, perform the loop and then, (n rows and n columns) for(i in 1:dim(mymat)[1]) # for each row { for(j in m and n, the matrix creation and its transformation into a dataframe only once A friend asked me whether I can create a loop which will run multiple regression models. She wanted to evaluate the association between 100 dependent variables (outcome) and 100 independent variable (exposure), which means 10,000 regression models.

Try:

rep(c(1:((nrow(df)/5)+1)), each=5, length.out=dim(df)[1])

Which gives:

> df$Increment<-rep(c(1:((nrow(df)/5)+1)), + each=5, + length.out=dim(df)[1]) > df state Value Increment 1 a 1 1 2 b 2 1 3 a 3 1 4 c 4 1 5 a 5 1 6 e 6 2 7 f 7 2 8 w 8 2 9 f 9 2 10 s 10 2 11 e 11 3 12 r 12 3 13 s 13 3 14 s 14 3

Where `df`

is:

dt = read.table(text = "state Value a 1 b 2 a 3 c 4 a 5 e 6 f 7 w 8 f 9 s 10 e 11 r 12 s 13 s 14", header=T)

**Creating a for loop to sum column values; how to increment between ,** I currently have a 1920x1080 matrix that is read into R using read.csv. I am trying to sum the first 10 items of each column, save it to a Rather than using a for loop, I would use one of the functions designed to iterate over a list or matrix df <- data.frame(V1 = seq(1,15), V2 = seq(2,16), V3 = seq(3,17)) df A tutorial on loops in R that looks at the constructs available in R for looping. Discover alternatives using R's vectorization feature. This R tutorial on loops will look into the constructs available in R for looping, when the constructs should be used, and how to make use of alternatives, such as R’s vectorization feature, to perform your

try:

dt = read.table(text = "state Value a 1 b 2 a 3 c 4 a 5 e 6 f 7 w 8 f 9 s 10 e 11 r 12 s 13 s 14", header=T) dt$Increment<- unlist(lapply(1:ceiling(nrow(dt)/5), function(x) rep(x, 5) ))[1:nrow(dt)] dt

**12 Useful Pandas Techniques in Python for Data Manipulation,** Learn Pandas techniques like impute missing values, binning, pivot, sorting, visualize, etc. Each Pandas index is made up of a combination of 3 values. is super important, what if I predict loan status to be Y for ones with credit history and N otherwise. #12 – Iterating over rows of a Pandas Dataframe. Loop over data frame rows Imagine that you are interested in the days where the stock price of Apple rises above 117 . If it goes above this value, you want to print out the current date and stock price.

**Loop over data frame rows,** Loop over data frame rows. Imagine that you are interested in the days where the stock price of Apple rises above 117 . If it goes above this value, Repeating things: looping and the apply family. 18 March 2013. Previously we looked at how you can use functions to simplify your code.Ideally you have a function that performs a single operation, and now you want to use it many times to do the same operation on lots of different data.

**Efficient accumulation in R – Win Vector LLC,** As we do work copying each row in each data frame (since in R data frame need to manipulate n rows to collect n rows into a single data frame) as n gets large. In some specialized situations (where value visibility is sufficiently limited) R can avoid a Slowest is the incremental for-loop accumulation. Table Row To Variable Loop Start KNIME Base Nodes version 4.1.3.v202005112252 by KNIME AG, Zurich, Switzerland This node uses each row of a data table to define new variable values for each loop iteration.

**ASP.NET Validation of viewstate MAC failed,** It was all good and suddendly we are receiving the error message below: R :Looping through each 5 rows of data frame and imputing incremental value ## affairs age yearsmarried religiousness education occupation rating ## 4 0 37 10.00 3 18 7 4 ## 5 0 27 4.00 4 14 6 4 ## 11 0 32 15.00 1 12 1 4 ## 16 0 57 15.00 5 18 6 5 ## 23 0 22 0.75 2 17 6 3 ## 29 0 32 1.50 2 17 5 5

##### Comments

- Possible duplicate of R - Make a repetitive sequence with 'rep'
- I get that it's an unclear question, but maybe whoever has downvoted all 5 answers so far could also explain what's wrong with the question and/or answers. For the OP: it's helpful to at least give a clear sense of the logic of what you're trying to do, and include the code you've tried so far
- does not give desired output