HRDataProcessing

Use C# to process HR data

Goals :

• Practice:
  • Github version control.
  • C#.
  • Process data.

Reflections: Why use C# instead of C++ ?

1. Data Binding & Reflection:

   • C#: Built-in reflection and data binding support.
   • C++: No built-in reflection, requires third-party libraries.

2. Language Features:

   • C#: Supports attributes (e.g., [TypeConverter]).
   • C++: No attribute-based reflection, manual coding.

3. Garbage Collection:

   • C#: Automatic garbage collection in .NET.
   • C++: Manual memory management with new, delete.

4. Built-in Libraries:

   • C#: Rich libraries (e.g., CsvHelper).
   • C++: Third-party libraries, more manual work.

5. Ease of Use:

   • C#: Declarative system with attributes.
   • C++: Manual serialization, more error-prone.

References :

Title: HR Analytics Dataset Source: Kaggle - HR Analytics Dataset File: Cleaned_HR_Data_Analysis.csv Description: This dataset provides information about employee satisfaction, department, age, tenure, salary, and whether an employee left the company.

The dataset contains the following columns: EmployeeID: Unique ID for each employee Age: Age of the employee Gender: Gender of the employee Department: Department where the employee works DistanceFromHome: Distance of the employee's home from the workplace EmployeeSatisfaction: Level of employee satisfaction (scale: 1 to 10) Salary: Salary of the employee Attrition: Whether the employee has left the company (Yes/No)

This dataset is used for practice.

Link: https://www.kaggle.com/datasets/hopesb/hr-analytics-dataset?resource=download&select=Messy_HR_Dataset_Detailed.csv

License This dataset is provided by Kaggle under the Kaggle Terms of Service. Make sure to check and comply with the licensing terms before using the dataset.