Sort / Manipulation Layer
Sort entire DataFrame based on values in specified columns. Similar to pandas' sort_values() or SQL's ORDER BY.
Supports:
- Multi-column sorting
- Mixed ordering (asc/desc)
- Null value placement
Example with two columns: Sort by: Region(asc), Sales(desc)
Before:
| Region | Sales |
|---|---|
| B | 100 |
| A | 150 |
| C | 80 |
| A | 120 |
After:
| Region | Sales |
|---|---|
| A | 150 |
| A | 120 |
| B | 100 |
| C | 80 |
Common applications:
- Hierarchical ordering
- Priority sequencing
- Rank-based analysis
- Performance ordering
- Category grouping
- Time-based sequencing
- Value-based organization
- Multi-criteria sorting
Table
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Table
Columns
[, ...]Ordered list of columns defining sort hierarchy. Examples:
- [Category(asc), Value(desc)]
- [Date(asc), ID(asc)]
- [Priority(desc), Name(asc)] Earlier columns take precedence in sorting
Select
columnColumn to include in sort criteria. Common uses:
- Primary grouping fields
- Numeric ranking values
- DateTime sequences
- Categorical hierarchies
Order
enumSort direction for each column. Determines whether values are arranged from smallest to largest or vice versa.
Ascending ~ Descending ~
Sort from lowest to highest. Examples:
- Alphabetical (A to Z)
- Numeric (1 to 999)
- Temporal (oldest to newest)
- Priority (low to high)
Sort from highest to lowest. Examples:
- Reverse alpha (Z to A)
- Numeric (999 to 1)
- Temporal (newest to oldest)
- Priority (high to low)
NullsLast
boolControl null value placement in sort order:
false(default): Nulls firsttrue: Nulls last Affects all sorted columns consistently