SELECT column AS in pandas

Posted by Kevin

Selecting one or more columns with an alias from a table in SQL, translated to Python's pandas.

Selecting a single column with an alias

In SQL:

SELECT 
  column_1 AS alias_1 
FROM 
  table;

In pandas:

table
    .rename({'column_1': 'alias_1'}) 
    ['alias_1']

Selecting multiple columns with an alias

In SQL:

SELECT 
  column_1 AS alias_1, 
  column_2 AS alias_2 
FROM 
  table;

In pandas:

table 
    .rename({'column_1': 'alias_1', 'column_2': 'alias_2'}) 
    [['alias_1', 'alias_2']]

Selecting aggregations with an alias

In SQL:

SELECT 
  column_1, 
  AVG(column_2) AS agg_alias_1, 
  AVG(column_3) AS agg_alias_2 
FROM 
  table 
GROUP BY 
  column_1;

In pandas:

table 
    .groupby('column_1') 
    .agg(agg_alias_1=('column_2', 'mean'), agg_alias_2=('column_3', 'mean'))

References