Analyse 2 Million Records of employees of a Multinational Company (MNC) with Python
Project Video available on YouTube - https://youtu.be/fykrwQD3HR4
Download Dataset - https://www.kaggle.com/datasets/rohitgrewal/hr-data-mnc/data
Connect with me on LinkedIn - https://www.linkedin.com/in/rohit-grewal
In this project, we have analysed the big dataset with Python.
This dataset contains HR information for employees of a multinational corporation (MNC). It includes 2 Million (20 Lakhs) employee records with details about personal identifiers, job-related attributes, performance, employment status, and salary information.
The dataset can be used for HR analytics, including workforce distribution, attrition analysis, salary trends, and performance evaluation.
This data is available as a CSV file. We are going to analyze this data set using the Pandas.
This analyse will be helpful for those working in HR domain.
There are multiple questions given that we answered with Python :
Q.1) What is the distribution of Employee Status (Active, Resigned, Retired, Terminated) ?
Q.2) What is the distribution of work modes (On-site, Remote) ?
Q.3) How many employees are there in each department ?
Q.4) What is the average salary by Department ?
Q.5) Which job title has the highest average salary ?
Q.6) What is the average salary in different Departments based on Job Title ?
Q.7) How many employees Resigned & Terminated in each department ?
Q.8) How does salary vary with years of experience ?
Q.9) What is the average performance rating by department ?
Q.10) Which Country have the highest concentration of employees ?
Q.11) Is there a correlation between performance rating and salary ?
Q.12) How has the number of hires changed over time (per year) ?
Q.13) Compare salaries of Remote vs. On-site employees — is there a significant difference ?
Q.14) Find the top 10 employees with the highest salary in each department.
Q.15) Identify departments with the highest attrition rate (Resigned %).
#python #dataanalysis #datascience