![]() Note however, that this approach is subject to change with the next version 0.6.0 of dplyr (see e.g. dots argument in the standard evaluation version: cols % rename_(.dots = cols) If you want to use dplyr's rename function, it would be best to create a named vector / list and call it using the. It's still a bit over my head, unfortunately, but I can see that it's doable >_> If, however, you need something that automatically appends ".xxx" to whatever column name is supplied to it, I recommend you have a close look at that section. Rename(!!paste("Sepal.Length", "xxx", sep = ".") := Sepal.Length) So if you're happy to do that manually, you can just: df %>% Selecting by position is not generally recommended, but rename()ing by position can be very useful, particularly if the variable names are very long, non-syntactic, or duplicated. > df1 %>% rename(!!newname := value, !!newname2 := index) There are now five ways to select variables in select() and rename(): By position: df > select(1, 5, 10) or df > select(1:4). In my simpler use case, I just needed to rename a column to the value of a string: > df1 = data_frame(index = 1:5, value = c(10, 20, 30, 40, 50)) I'm a little late to the party on this, but after staring at the programming vignette for a long time, I found the relevant example in the Different input and output variable Write a function that takes your old column names as input and returns your new column names as output, and you're done :) Previously, e.g., funs( paste0(., to_app) )ĮDIT: these days, I'd recommend using dplyr::rename_with, as per answer. This list() coding replaces the previous funs() coding starting in dplyr_0.7.0. rename_at(df, vars( contains("Length") ), list( ~paste0(., ".xxx") ) ) You can also use the select helper functions to choose variables for renaming, such as contains. rename_at(df, cols, list( ~paste0(., to_app) ) ) This has been superseded in version 1.0.0, which means there are new functions to use as above but this particular function is not going away. Sepal.Width Įarlier versions of dplyr use rename_at(). You can use the tidy-select function all_of() (or others) to choose columns. The function argument comes before the column argument. cols = c("Sepal.Length", "Petal.Length")įor dplyr_1.0.0, use rename_with(). In your example, the paste0 function can be used to append on the appropriate suffix to each column. To suppress this warning you can use the following command.You can use the rename_at() function for this (starting in dplyr_0.7.0) or rename_with() (starting in dplyr_1.0.0).įor example, you can pass the variables you want to rename as strings. #`summarise()` regrouping output by xxx (override with `.groups` argument) ![]() ![]() #`summarise()` ungrouping output (override with `.groups` argument) Since dplyr >= 1.0.0 version you may get the following warnings. We are calculating count and mean of variables Y2011 and Y2012 by variable Index. The snapshot of first 6 rows of the dataset is shown below. This dataset contains 51 observations (rows) and 16 variables (columns). To download the dataset, click on this link - Dataset and then right click and hit Save as option. Note : This data do not contain actual income figures of the states. In this tutorial, we are using the following data which contains income generated by states from year 2002 to 2015.
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