Data Analytics related Job Scraping, Analysis and Visualization

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Project Overview 🕮

It was exciting to start a career in data analysis, but I had a lot of questions. In addition to the various jobs related to “data analytics” I found out which regions of the world has the highest data analyst job demand, which would result in higher pay and better working conditions. What distinguishes working as a data analyst as an entry, junior, or senior levels in a company. We will also observe the requirements needed to be hired in any of the job levels. 🚀 📈 ### Languages and Tools 👨‍💻

  Languages

Languages	Usage
Python 3.11.0	Programming Language For data cleaning
SQL (Structure query Language)	Programming Language For manipulation and visualization

  Tools

Tools & Environment	Usage
SQL Server	Data cleaning.
Jupyter NoteBook	An open-source IDE used to create the Jupyter document.
Power BI (Power query, DAX)	Data visualization tool.
Git	A version control system to manage and keep track source code history.

Libraries 🐱‍💻

• BeautifulSoup for data scraping.
• requests to verify website server the status.
• numpy for mathematical operations on arrays.
• datetime for date manipulation.
• pandas to perform data manipulation and analysis.
• seaborn for data visualization and exploratory data analysis.
• plotly to create beautiful interactive web-based visualizations.
• plotly express easy-to-use, high-level interface to Plotly.

About the Data

• Job Title — The name of the available job
• Company Name — The name of the company with the job vacancy
• Location — It contains the Physical Location of the company and if the job is remote
• Level — It’s the Job level, if it is a junior, mid or senior role
• Job Type — Is the job a full-time or internship role
• Salary Range — The pay range (some columns are in yearly range, while some are in hourly range)
• Required Skills — Necessary skills an applicant must have before applying
• Benefits — The benefits that comes with the job

Problem Statement

• Which skills are the most demanded among companies, relative to the Level of employment (Senior, Mid, Executive, Entry)?

• which data analytics related position and level has the highest job placements?

• Which job type is suitable (Full time, Part time, Hybrid)?

• How likely is it to be employed as a remote or onsite analyst?

• Which companies have the highest number of job posts?

Project Link

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Running the project

To run the (.ipynb) file, use Notebook or Google Colab, Power BI for the (.PBIX) file and sql server to run the sql queries.

Support

For support, email njimonda.co@gmail.com.

Author

• @njimonda

Badges

Contributing to this project

Contributions are always welcome!

Please adhere to this project's code of conduct.

Acknowledgements

• Awesome Readme Templates
• Awesome README
• How to write a Good readme