- Advanced Operations in the Tabular Model
- Aggregating Data
- Grouping Data
- Combining Tables
- Missing Data
|Monday||Chapter 8, 8.1||none|
|Wednesday||Chapter 8, 8.2 to 8.3.2||none|
|Friday||Chapter 8, 8.3.3 to end||TBD|
|HW||Day Out||Day Due||Contents|
|HW_2.1||Tuesday||Friday||Aggregation and Grouping, Mutations|
|HW_2.2||Friday||Monday||Table Combining and Missing Data|
Quiz 1, covering Python review (lists, dictionaries, filesystems) and 2D representations, list comprehensions and functions as objects, row and column access operations on
pandas data frames.
Goal of the week is to deepen our understanding and use of operations in the tabular model as realized by the abilities of the
Monday: Focus on data aggregation and grouping, starting from simple aggregation of column vectors and proceeding with variations (uniform and non-uniform) aggregation on subsets of columns in a data frame and concluding with group partitioning that combines with
Tuesday: Quiz 1, as described above.
Wednesday: Here, we will cover mutations to change values, delete rows or columns, add rows and columns, and even conditionally update value for only some rows. Then we will move on to the simpler forms of combining tables.
Friday: The topics here will involve the more complex combining of tables in a way that integrates them together with operations of join and merge. We will also see some operations that allow us to deal with missing data.