Python Missing Data Script | Dataford Interview Questions

Write a Python script to handle missing data in a large dataset.

Implement handle_missing_data(records, numeric_fields, categorical_fields). Each record is a dictionary; a missing value is represented by None or an absent key. Return new records, replacing numeric missing values with their field mean and categorical missing values with their most frequent value. Break categorical frequency ties by choosing the lexicographically smallest value. Use 0.0 for an entirely missing numeric field and an empty string for an entirely missing categorical field. Do not mutate the input records.

Constraints

1 <= len(records) <= 5000
Each record is a dictionary with string keys
Numeric field values are integers or floating-point numbers when present
Categorical field values are non-empty strings when present
A field may be absent from a record, which is treated as missing
The input records must not be mutated

Function Signature

def handle_missing_data(records, numeric_fields, categorical_fields):

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Problem

Write a Python script to handle missing data in a large dataset.

Constraints

1 <= len(records) <= 5000
Each record is a dictionary with string keys
Numeric field values are integers or floating-point numbers when present
Categorical field values are non-empty strings when present
A field may be absent from a record, which is treated as missing
The input records must not be mutated

Function Signature

def handle_missing_data(records, numeric_fields, categorical_fields):

Your question is Python Missing Data Script. Start with the requirements 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.