| warp_equivalent <- function(warpfactor, originalseries = FALSE) { | |
| if (originalseries == TRUE) { | |
| v <- (warpfactor^3) * 299792458 # speed of light -- 299792458 m/s | |
| } else if (originalseries == FALSE) { | |
| if (warpfactor > 9.0 & warpfactor <= 10.0) { | |
| x <- -0.5 * log10(10 - warpfactor) | |
| } else { | |
| x <- 0 | |
| } | |
| v <- (warpfactor^((10/3) + x)) * 299792458 |
| # minimal dataset | |
| dat <- data.frame(a = c(1, 5, 2), | |
| b = c(5, 2, 9), | |
| c = c(4, 3, 1)) | |
| rowMeans(dat) | |
| # [1] 3.333333 3.333333 4.000000 | |
| do.call(rbind, lapply(seq_len(nrow(dat)), function (k) {mean(as.numeric(dat[k, ]))})) |
| library("plyr") | |
| library("dplyr") | |
| ### create some sample data | |
| set.seed(20) | |
| dat <- data.frame(lake = c(rep("Muddy", 6), rep("Clear", 6)), | |
| host = c(rep(c("a", "b"), 6)), | |
| var = sample(c(0, 1, 2), 12, replace = TRUE), | |
| stringsAsFactors = FALSE) | |
Where I live there are a lot of little drive-thru coffee shops that like to advertise special beverages. Many of these disturb me. Here is a non-comprehensive list of ones I have seen:
| library("shiny") | |
| library("ggplot2") | |
| shinyServer(function(input, output) { | |
| output$myplot <- renderPlot({ | |
| ## Create a boxplot with optional jittering | |
| p <- ggplot(iris, aes(x = Species, y = Petal.Length)) + |
| # In response to: https://twitter.com/duffy_ma/status/628300075110936576 | |
| df <- data.frame(x=1:10, y = 1:10) | |
| library("plyr") | |
| df$y <- mapvalues(df$y, from = c(5), to = c(NA)) # make sure to keep `y` column numeric | |
| lengthdata <- length(df$x) | |
| for(i in 1:(lengthdata-1)) { | |
| if (is.na(df$y[i])) { # use is.na to test for NAs |
| library("ggplot2") | |
| library("dplyr") | |
| ########################################################### | |
| #### This does not work to create stacked area chart #### | |
| ########################################################### | |
| ## Create data | |
| set.seed(40) | |
| dat <- data.frame(x = rep(c(1:10), 3), |
| ## Load ggplot package | |
| library("ggplot2") | |
| ## Create sample data | |
| dat <- structure(list(x = c(2.69753522456158, 9.77329733015504, | |
| 0.579014160879888, 6.01934352936223, | |
| 5.53224114519544, 7.52123757028021, 1.1418573057279, | |
| 5.81543114883825, 1.98635061332025, | |
| 8.98725295660552), | |
| y = c(1.1341254551895, 8.69686821205542, 1.0851298507303, |
| B0S2 | B0S3 | B0S4 | |||||||
|---|---|---|---|---|---|---|---|---|---|
| abundance | percent cover | height | abundance | percent cover | height | abundance | percent cover | height | |
| 5 | 50 | 71 | 8 | 30 | 9 | 45 | |||
| 5 | 3 | 47 | 1 | 1 |
| ## Load tidyverse package, which contains ggplot2, dplyr, tidyr, etc. | |
| library("tidyverse") | |
| ## Create some data | |
| set.seed(432) | |
| dat <- tibble(fert = c(rnorm(n = 10, mean = 0.6, sd = 0.2), | |
| rnorm(n = 10, mean = 0.4, sd = 0.2)), | |
| treat = rep(c("25-25", "28-28"), each = 10)) | |
| ## Plot boxplots with points on top + yellow X for mean & legend |