I have a dataframe that has missing values at each column, but at different rows. For simplicity, let’s see the following dataframe (real dataframe is much more complex): first_column <- c(1, 2, NA,NA) second_column <- c(NA, NA, 4,9) df <- data.frame(first_column, second_column) and we get: first_column second_column 1 1 NA 2 2 NA 3 NA… Read More remove missing values from dataframe and reshape the dataframe with the non-missing ones

I have this simple data frame, colx <- c(2002-01, 2002-02, 2002-03, 2002-04) cola <- c(10, 20, NA, 40) colb <- c(NA, NA, NA, 400) colc <- c(1000, 2000, 3000, 4000) df <- data.frame(colx, cola, colb, colc) df > df colx cola colb colc 1 2001 10 NA 1000 2 2000 20 NA 2000 3 1999… Read More Wide to long omitting the early NAs

Let’s say I have a dataframe like this – for each sample (which represents an area), there are ten habitat classes (1:10) which can be present in the sample. The dataframe doesn’t have an entry for each one, only the ones present in each sample. data <- data.frame( sample.label = c(1, 1, 1, 2, 3,… Read More Reshape of dataframe where all values not present

Probably a tidyr or a reshape2 question. I have this type of a data.frame: df <- data.frame(group = c("A","B","C","D"), id1 = c("AV14D","BV29",NA,NA), id2 = c(NA,"BD1",NA,NA), id3 = c("AJ31","BJ1",NA,NA), n = c(2,4,NA,NA), stringsAsFactors = F) which has a row with 3 IDs and a count for each group. I want to transform it to a single… Read More Spread a dataframe and relabel column names