Analysis of Employees Reviews Accenture Project

Click on the link below to see the rendered visuals of the plots/graphs

https://nbviewer.jupyter.org/github/majd1239/Analysis-of-Employees-Reviews-of-Accenture/blob/master/Accenture_Reviews_Analysis.ipynb

This was my project in preparation for Accenture AcnTechBuild talent recruitment event. We were told to prepare a pre-built piece of software to present at the event and then participate in an analytics build session. This project led to a summer internship offer from Accenture.

I wrote the project from scratch. I wanted to present a code that has value in it. I chose to do a data analysis and visualization using Python. My first step was to search for a relevant data to work on. The company's reviews by its employees on GlassDoor was the perfect choice. It provides the company a good feedback on what its employees are thinking.

The GlassDoor API does not provide a way to extract the reviews of a company. So I build a Python script using Selenium framework that scrapes all the reviews through webcrawling and write them to a csv file. The actual script can be viewed in the GlassDoor-Reviews-Scrapper repository.
After collecting the reviews and parsing them into proper headers in a csv file, I used Pandas Python framework to created a dataframe.I then cleaned the data and categorized the reviews by five major job fields: Interns, Technology, Consultants, Managers, Analytics and Other.
The following visuals where then created:

  • A pie chart visualizing the total reviews number segmented by the five job fields.
  • A bar chart was created to visualize the average rating per year of former vs current employees.
  • A plot line showing a time series of the incline/decline average rating per job field over the years.
  • A sentimental analysis was done on the reviews. They were sorted by the most common word used. A bar
    char visualize the top N Pros or Cons topics. The number of topic is dynamic and can be adjusted.
  • A scatter plot was created to visulize the actual content of the reviews sorted by the topics along a
    timeline x-axis and an average rating y-axis. The scatter can be filtered according to the desired selected
    topics and when hovered, it will display the Review content plus that employee advice to the management.