nxcals.api.extraction.data.builders.DataFrame.orderBy

DataFrame.orderBy(*cols: Union[str, Column, List[Union[str, Column]]], **kwargs: Any) → DataFrame

Returns a new DataFrame sorted by the specified column(s).

New in version 1.3.0.

Parameters:

cols (str, list, or Column, optional) – list of Column or column names to sort by.
ascending (bool or list, optional) – boolean or list of boolean (default True). Sort ascending vs. descending. Specify list for multiple sort orders. If a list is specified, length of the list must equal length of the cols.

Examples

>>> df.sort(df.age.desc()).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> df.sort("age", ascending=False).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> df.orderBy(df.age.desc()).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> from pyspark.sql.functions import *
>>> df.sort(asc("age")).collect()
[Row(age=2, name='Alice'), Row(age=5, name='Bob')]
>>> df.orderBy(desc("age"), "name").collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]
>>> df.orderBy(["age", "name"], ascending=[0, 1]).collect()
[Row(age=5, name='Bob'), Row(age=2, name='Alice')]