Selecting a conditional column in SQL using CASE WHEN, translated to pandas.

Selecting a column on a single condition

In SQL:

SELECT 
  column_1, 
  CASE WHEN column_2 > 10 THEN "Comment" ELSE "Other comment" END AS comment 
FROM 
  table;

In pandas:

table 
    .assign(comment = table['column_1'] 
    .apply(lambda column_1: 'Comment' if column_1 > 10 else 'Other comment')) 
    [['column_1', 'comment']]

Selecting a column on multiple conditions

In SQL:

SELECT 
  column_1, 
  CASE WHEN column_1 > 10 THEN "Comment" WHEN column_1 < 1 THEN "Other comment" ELSE "Another comment" END AS comment 
FROM 
  table;

In pandas:

table 
    .assign(comment = table['column_1'] 
    .apply(lambda column_1: 'Comment' if column_1 > 10 else ('Other comment' if column_1 < 1 else 'Another comment'))) 
    [['column_1', 'comment']]

References