Write a Python script using Pandas and NumPy to load two separate dataframes, clean missing values, and merge them on a specific key.
For this SQL version, clean the nullable attributes and combine records using record_key. Exclude rows where the source record key is NULL.
dataframe_arecord_key, subject_name, measurement, category, and review_statusrecord_key ascending| Column | Type | Description |
|---|---|---|
| record_key | INTEGER | Identifier used to match records across both datasets |
| subject_name | VARCHAR(100) | Subject or record name |
| measurement | NUMERIC(12,2) | Numeric measurement associated with the record |
| Column | Type | Description |
|---|---|---|
| record_key | INTEGER | Identifier used to match records across both datasets |
| category | VARCHAR(100) | Classification associated with the record |
| review_status | VARCHAR(50) | Current review status |