
Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that you can bring them under control and analyze them effectively. The key goal in data wrangling is transforming non-tidy data into tidy data. This course covers many of the critical details about handlin
Shannon Ellis, PhD
UC San Diego
Stephanie Hicks, PhD
Johns Hopkins Bloomberg School of Public Health
Roger D. Peng, PhD
University of Texas, Austin
Carrie Wright, PhD
Biostatistics