About the course:

The Data Wrangling and Visualization course is designed to help students understand that the heavy lifting in any analysis happens before the analytical procedure starts. Data wrangling is the process of changing the structure and format of raw data until the data are compatible with sometimes rigid requirements for analysis. Data wrangling also includes a quick sanity check of data quality. Data Visualization will give students an understanding and appreciation of the power in representing data graphically. Objectives: Extract important data from an existing data set. Data table manipulations (stacking, splitting, summarizing, and joining) to change table format. Screen data to improve data quality and reduce noise. Decide which data to include and exclude from their analyses. Explain required input formats for various analyses. Understand the impact that metadata has on analyses. Create various methods of visualizing data using common tools: boxplot, histogram, scatterplot, line chart, treemap, heat map, Pareto chart, sparklines, dynamic charts. Attach meaningful statistics and analyses to the appropriate visualization.