Data Management and Preparation Using R
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.
What you'll learn
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.
Table of contents
About the author
Martin studied biostatistics and worked for several pharmaceutical companies before he became a data science consultant and author. He published over 15 courses on R, Tableau 9 and other data science related subjects. His main focus lies on analytics software like R and SPSS but he is also interested in modern data visualization tools like Tableau. If he is not busy coding, blogging or working out new teaching concepts you may find him skiing or hiking in the Alps.