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Load data – check structure – convert – analyse.

Data class conversion is essential to gaining the right result… especially if you have left stringsAsFactors = TRUE. The worst thing you can do is feed factor data into a function when you expected it to be characters.

If system memory is not a concern, I prefer to read data in as character strings and then convert accordingly, I view this as a safer option… it forces you to take stock of each field.

There are many ways to perform data conversion, for example, you can use transfrom() in base R or dplyr’s mutate() family of functions. For a single column conversion I prefer to use mutate but for multiple conversions I use mutate_each() and just specify the relevant columns. This avoids repeating the column names in code.

I still need to do some bench-marking to see which setup is faster, but for now I see mutate_each() as the cleanest, aesthetically at least. I have also included an example of ‘all column’ conversion.