EXECUTIVE SUMMARY
The analysis of salaries fo over 300,000 employees indicates that there are substantial distortions:
- Assistant Engineers, Senior Engineers and Tecnique Leaders have almost identical average salaries.
- Staff and Senior Staff also have nearly identical average salaries, and both make nearly 20% more than all engineers.
Recommendation: I highly recommend that the compensation committie conduct a thorough review of the salary policies to avoid talent flight and/or a full scale revolution of the engineers. They are armed with nurf guns and are known to be dangerous when agitated.
REPOSITORY NAVIGATION
- Database Visual Schemata presents a visual diagram of the employee database.
- Database Postgre Schematic contains the Postgre SQL code to set up database tables.
- Database Queries contains Postgre SQL to explore the data.
- Data Analysis in Jupyter Notebook contains code to import the database data into Pandas, with a histogram of salary ranges and average salary by position.
OBJECTIVE
Analyze compensation data for over 300,000 employees:
- Create code to set up a database using Postgre SQL, import data from csv files, and run queries
- Import data into a Jupyter Notebook
- Create code to analyze and plot compensation data
- Provide recommendations to the corporate compensation committee
DATA
- Create conceptual database design for human resources data
- Structure data in a Postgre database and import data from csv files
- Run queries
- Export data from the Postgre database to a Jupyter Notebook to analyze and plot
DEPENDENCIES
- from sqlalchemy import create_engine
- from sqlalchemy.dialects import postgresql
- from config import pgadmin_pw
- import pandas as pd
- import matplotlib.pyplot as plt
PANDAS ANALYSIS
CONCLUSIONS
- Assistant Engineers, Senior Engineers and Tecnique Leaders have almost identical average salaries.
- Staff and Senior Staff also have nearly identical average salaries, and both make nearly 20% more than all engineers.
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