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1. stackoverflow.com › questions › 51393469Better alternatives For Loop R - Stack Overflow

   stackoverflow.com › questions › 51393469

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   Jul 18, 2018 · I am storing a value in column c based on this criteria. There are 4million rows in my dataframe and this takes 2 days to finish. for ( i in 1:NROW(df)) {. df$c[i+1] <- df$a[i] + df$b[i] - df$a[i+1] print(i) } Are there any alternatives to this for loop that can accomplish what I am doing much faster. Thanks in advance.

   Code sample

   set.seed(2017)

   df <- data.frame(

     a = sample(100, 10^6, replace = T),

     b = sample(100, 10^6, replace = T))

   library(microbenchark)...

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2. stackoverflow.com › questions › 14519681Alternative to loops in R - Stack Overflow

   stackoverflow.com › questions › 14519681

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   Jan 25, 2013 · Alternative loop. tao = 1000 L = (tao - 1) n = 10 V = 5 I = 10000 V_s = matrix(rnorm(I), I, 1) V_b = matrix(rnorm(I), I, 1) signal <- matrix(0, L, 1) for( j in (n:L)){ sapply(((j-n+1):j),function (tao) signal[j] = signal[j] + abs(V_s[tao] - V_b[tao])) signal[j] = (signal[j] / (n * V) ) }

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4. stackoverflow.com › questions › 8305809ide - Is there something like RStudio for Python? - Stack ...

   stackoverflow.com › questions › 8305809

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   Nov 29, 2011 · Eclipse PyDev, Jupyter, and Spyder/Anaconda are decent substitutes, but none of them are as easy to work with as RStudio. The code completion, shortcuts for switching areas, interactive installation of packages, tabs with repositioning of order, documentation pane, all make RStudio easier to use.

5. stackoverflow.com › questions › 68604367r - Is there an efficient alternative to table()? - Stack ...

   stackoverflow.com › questions › 68604367

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   Jul 31, 2021 · If a faster alternative to table() is required, including cross-tabulation, collapse::qtab(), available since v1.8.0 (May 2022) is a faithful and noticeably faster alternative. fcount() can also be used in the univariate case, and returns a data.frame.

6. stackoverflow.com › questions › 30494520Alternatives to nested ifelse statements in R - Stack Overflow

   stackoverflow.com › questions › 30494520

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   May 28, 2015 · For the x[logical] VS x[which(logical)], x[which(x)] is 3 ms on both versions of R, but x[x] is 5 ms on R-3.2.0 VS 12 ms on R-3.1.2. Looking at R-3.1.2's logicalSubscript VS R-3.2.0's logicalSubscript, it seems that R-3.2.0 avoids extended use of "%" in returning integer indices from the logical ones (to be -subsequently- used). –

7. stackoverflow.com › questions › 36378698alternative to `str()` in R - Stack Overflow

   stackoverflow.com › questions › 36378698

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   Apr 3, 2016 · There is the lobstr package by Hadley. Besides several other more or less helpful functions it includes lobstr::tree() which tries to be more predictable, compact and overall more helpful than str(). An important difference between the two is that str() is an S3 generic whereas lobstr::tree() is not.

8. stackoverflow.com › questions › 67368654Alternatives to loop in R - Stack Overflow

   stackoverflow.com › questions › 67368654

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   May 3, 2021 · parsedData <- data %>% group_by(*variable name you would like to group*) %>% summarise(. newVariable = *the components of your new variable*. ) However, the most important thing is to avoid loops. In case you need to loop something big, you could also take a look to sapply, apply, lapply, and mapply functions.