Data management and data preparation is a very important yet widely overlooked part of data analysis. Importing, selecting a proper class, cleaning, and filtering are all part of data preparation and will be taught in this course.
Have you ever encountered problems in data analysis just because the data was not clean, had a wrong format, or was simply messy? Data preparation is an immensely important yet overlooked field in data science. Most of the time of a data professional is not spent analyzing or visualizing, it is spent getting data ready as clean and well-structured as possible. R is a widely used open source tool with an active user community. This community created high quality add on packages for data preparation. In this course, Data Management and Preparation Using R, you will not only learn about data preparation in R Base, you will also learn about those add on packages that make R so powerful. First, you'll learn about data importing, cleaning, and structuring (selecting the right class). Next, you'll explore data querying. Finally, you will learn about dplyr, tidyr, reshape2 and data.table. At the end of this course, you will be able to select the right tools and efficiently perform data import, formatting, cleaning, and querying.
Martin is a trained biostatistician, programmer, consultant and data science enthusiast. His main objective: Explaining data science in a straightforward way. You can find his latest work over at: r-tutorials.com