pyspark.sql.DataFrame.select#

DataFrame.select(*cols)[source]#

Projects a set of expressions and returns a new DataFrame.

New in version 1.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colsstr, Column, or list: column names (string) or expressions (Column). If one of the column names is ‘*’, that column is expanded to include all columns in the current DataFrame.

Returns

Examples

>>> df = spark.createDataFrame([
...     (2, "Alice"), (5, "Bob")], schema=["age", "name"])

Select all columns in the DataFrame.

>>> df.select('*').show()
+---+-----+
|age| name|
+---+-----+
|  2|Alice|
|  5|  Bob|
+---+-----+

Select a column with other expressions in the DataFrame.

>>> df.select(df.name, (df.age + 10).alias('age')).show()
+-----+---+
| name|age|
+-----+---+
|Alice| 12|
|  Bob| 15|
+-----+---+