We want to save a dataframe that includes non-English characters. Much of the time, we use it to read in files, write to new files, or do various programmatic conversions. Those who use multiple languages (and yes, emojis count) quickly find that encoding bugs are– as Joshua Goldberg put it–“quite annoying and a time sink with little value gained after you make it out alive.” This means that any characters that cannot be represented in the computer’s native encoding become garbled. Rather than forcing UTF-8 on its users, many base R functions translate inputs into the native encoding, whether you ask it to or not. 1 To this day, Windows does not yet have full UTF-8 support, although Linux-based and web systems have long since hopped on the UTF-8 train.Įncodings in R may not have been so bad had the default encoding in base R not been native.enc. Unfortunately, the rise of UTF-8 occurred only after the establishment of core Windows systems, which were based on a different unicode system. In the early 90’s, some developers proposed UTF-8, a system that struck a balance between storage and support for many character sets (alphabets/characters in different languages). So, they came up with a system several systems. Once upon a time, computer scientists needed a way to store characters as bits (1’s and 0’s).
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