Webbför 2 dagar sedan · My goal is to create a binary column for each potential response in that column to determine whether that individual provided that response at all throughout the dataset. ... Here is a pure Tidyverse approach: ... First we create dummy binary variables from factor fruit, then we summarise across and find the max: Webb6 dec. 2024 · Method 1: Use as.factor() df$factor_variable <- as.factor(df$numeric_variable) This will convert the numeric variable to a factor variable …
Column-wise operations • dplyr - Tidyverse
WebbRe-convert character columns in existing data frame Source: R/type_convert.R This is useful if you need to do some manual munging - you can read the columns in as character, clean it up with (e.g.) regular expressions and then let readr take another stab at parsing it. The name is a homage to the base utils::type.convert (). Usage WebbA logical, integer, or character vector giving the elements to select. Alternatively, a function that takes a vector of names, and returns a logical, integer, or character vector of elements to select. : if the tidyselect package is installed, you can use vars () and tidyselect helpers to select elements. A vector, usually the same length as .x. thai thai indialantic menu
How to make all responses in a column into their own unique column …
Webb8 mars 2024 · How to Convert Multiple Columns to Numeric Using dplyr You can use the following methods to convert multiple columns to numeric using the dplyr package: Method 1: Convert Specific Columns to Numeric library(dplyr) df %>% mutate_at (c ('col1', 'col2'), as.numeric) Method 2: Convert All Character Columns to Numeric WebbRead in a file and simultaneously specify which columns should be read as factors: data <- read_excel (path = "myfile.xlsx", col_types=c (col2="factor", col5="factor))) Or this function would be excellent for many reasons, but I can't figure out how it's supposed to work. … synonyms for being ahead