Performing Data Analysis with Multiple Tools: Pandas, R and Deedle (F#/C#) 2016

Key Topics

• Mutating data frame objects
• Organizing information into data frames
• Data alignment between data frames
• Indexing data frames
• Joining data
• Handling missing data
• Accessing data from web services
• Reading and writing data from files and databases
• Slicing and subsetting data
• Reshaping of data (ie: pivoting and melting)
• Deriving aggregate results from data
• Grouping of data
• Resampling time series data into other frequencies
• Handling of time series information
• Moving and sliding windows statistics
• Shifting time series data
• Data visualization

Who should Attend

• IT VP and Development Managers
• Data Analysts Wanting to Learn any of the Covered Tools
• Application / Software Developers and Engineers
• Application / Software Architects
• Individuals or organizations interested in data science and how to derive meaning from data