Pivot and Merge in Python | Dataford Interview Questions

Explain how you use pivot and merge operations in Python for data preparation.

For this SQL exercise, express the same preparation pattern by combining entity profiles with validated observations and presenting monthly scores as columns.

Output

One row per entity, including entities without validated observations.
Columns: entity_id, entity_name, segment, jan_score, feb_score, and mar_score.
Use NULL when a validated score is unavailable. Order by entity_id ascending.

Schema

entity_profiles

Column	Type	Description
entity_idPK	INT	Unique entity identifier
entity_name	VARCHAR(100)	Entity display name
segment	VARCHAR(50)	Business segment assigned to the entity

prepared_observations

Column	Type	Description
observation_idPK	INT	Unique observation identifier
entity_id	INT	Entity associated with the observation
period	VARCHAR(7)	Observation month in YYYY-MM format
score	DECIMAL(6,2)	Prepared score for the period
validation_status	VARCHAR(20)	Validation state of the observation

Your question is Pivot and Merge in Python. Start with the requirements and the two tables in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem