R Tutorial: Turning numbers into strings

Want to learn more? Take the full course at https://learn.datacamp.com/courses/string-manipulation-with-stringr-in-r at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- A common use of strings is to report numerical results. You might, for example, want to report an estimate for the additional sales generated by each dollar spent on advertising. You've got the estimate stored in R, let's say one point three four zero one nine zero two nine one zero zero, but is that what you want in your report? No, you probably want something like $1.34. You might argue you can do this manually every time you need to, but doing this with code means its easy to automate, update and reuse in the future. You can always force a number to be a string with as.character(). But R won't do any formatting and will output to 15 significant digits, way more than you need in most cases. Instead I recommend using the functions format() or formatC(). They both give you control over how a number is represented as a string but take slightly different approaches. First let's do a quick review of fixed and scientific formats for numbers. In fixed format the decimal point is in a fixed place, between the tenths and ones digits. In scientific format, the decimal point can be anywhere, it is always displayed after the first digit, and then we use an exponent to describe its position. Take the distance six thousand, three hundred and seventy one kilometres. In fixed format it is simply In scientific format we would write it as six point three seven one times ten to the power three. That is, you take six point three seven one and multiply it by one thousand. Alternatively, you can think about taking six point three seven one and moving the decimal point three places to the right. The advantage of scientific notation is that very large and very small numbers can be written quite concisely. For example, the mass of the sun in kilograms