From the course: Complete Guide to R: Wrangling, Visualizing, and Modeling Data
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R in context
From the course: Complete Guide to R: Wrangling, Visualizing, and Modeling Data
R in context
- [Instructor] Any programming language or application is first and foremost a tool. And the general rule with tools is that you want to use the right tool for the job. That's true working in data science as well. You have a range of tools available for working with data, one of which is R. But there are other tools too, and I want to show you where R should be in your data science toolbox. The first and most obvious tool for working with data is a spreadsheet. I like to think of these as the universal data containers because they're everywhere and everybody uses them. Now, obviously, the common choices for spreadsheets include Microsoft Excel and Google Sheets, although there are many other possible choices. The reason spreadsheets are great tools is because they let you organize your data however you want. And they can sort and filter data, they can count and summarize data, and they can quickly make relatively sophisticated graphs. Truthfully, spreadsheets are probably sufficient…
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