Coding Exercise: Clean the Employee Survey Data
Practice fixing messy real-world data using pandas to make it analysis-ready.
We'll cover the following...
We'll cover the following...
Scenerio
You’re a junior data scientist at a mid-sized company. HR has just shared the results of an internal employee satisfaction survey, but the data is messy! Your job is to clean and prepare this dataset for further analysis. You’ll need to handle duplicated data, missing values, and normalize certain columns, just like in a real-world workplace.
Dataset
Here’s a sample DataFrame (df) you’ll work with:
Employee Data
employee_id | department | tenure_years | satisfaction_level | remote_status |
101 | HR | 2 | 4.2 | Yes |
102 | HR | 3 | NaN | No |
103 | Finance | 4 | 3.9 | Yes |
104 | NaN | NaN | 2.5 | No |
104 | Finance | NaN | 2.5 | No |
Task
Clean the df DataFrame by performing the ...