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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.
Jul 18, 2018 · Let's compare the following three methods in terms of performance/runtime. We use sample data consisting of 10^6 entries for a and b. a = sample(100, 10^6, replace = T), b = sample(100, 10^6, replace = T)) method_lag = {. df <- mutate(df, c = lag(a) + lag(b) - a) }, method_base = {. df$c <- NA.
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Jul 6, 2020 · Is there any function like View() that displays data similarly but allows for resizing of row heights (to display >1 line of long strings), and perhaps some smarts to allow us to explore list columns in data.frames? One idea is a function that takes a data.frame argument, writes it as a temp file, and starts a shiny app that displays the data.
Jan 25, 2013 · My primary concern is speed, as I need to create a loop around the entire algorithm and plot in different V and n sizes for some further analysis. Thanks for your help. Alternative loop. sapply(((j-n+1):j),function (tao) signal[j] = signal[j] + abs(V_s[tao] - V_b[tao])) signal[j] = (signal[j] / (n * V) ) Original loop.
Nov 9, 2020 · However, I find myself in a situation where using bind_rows on an extremely large list of data frames takes much longer than I'd like. Does anyone know of a faster alternative? r. dplyr.
May 28, 2015 · To sum up, a way to work on the "list" structure of a "data.frame" and to stop computations when we find a "1", could be a loop like the following: ff = function(x) { x = as.list(x) ans = as.integer(x[[1]]) for(i in 2:length(x)) { inds = ans == 0L if(!any(inds)) return(ans) ans[inds] = i * (x[[i]][inds] == 1) } return(ans) }
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.
