Reshaping

Most of the datasets we meet in real life need a significant amount of restructuring before commencing with the actual purpose e.g. data analysis. In this section, we cover how to modify the structure of a dataset.

This section is organized as follows:

  • Joining: Combining information from multiple tables or data frames into a single table or data frame. We use the SQL-style joins: Left Join, Right Join, Inner Join, and Full Join, to specify how the data should be combined.
  • Appending: Appending multiple data frames to each other either vertically where we bind the rows of multiple data frames into a longer data frame, or horizontally where we bind the columns of multiple data frames into a wider data frame.
  • Pivoting: Converting a table or a data frame between long and wide forms. In pivoting, we often move information from column names to columns and vice versa.
  • Transposing: Converting the rows of a data frame into its columns and vice versa.
  • Nesting where we cover how to create a data structure where data frames are nested as cells in data frames as well as unnesting nested data frames into a flat data frame structure.
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I/O