I scraped more than 5000 “DATA ANALYST” Jobs posted in the United States in 2023 to gain insight into the current state of the job market. WHAT DID I FIND? Top Skills? Salary? Degree Requirements? *Link to the scraped data and the python code at the end if you want to do your own analysis. Dataset Total Number of Job postings included in the analysis = 5359 I cleaned the dataset to only Include Job Titles that had the keywords “Data” or “Analyst” in them —…

In a world where technology has taken over our lives, one man found himself spiraling down a dangerous path. A path that would consume him and leave him in a constant state of uncertainty and fear. This man had stumbled upon a new form of artificial intelligence, one that promised…

This post will take you through how to take a python app built using the streamlit package, dockerize it and deploy it to Google App Engine. What you Need: git — To clone the GitHub repository that contains a streamlit app which is ready to be deployed. Docker — To bundle application code, requirements…

In this post we will write a python script that fetches stock market data using the yfinance package, processes the data and uploads the data into a Google BigQuery table which can be used for further analysis or visualization. Fetch Stock Market Data To fetch the data of a particular stock, we need the…

What is BigQuery? -Serverless -Highly Scalable -Highly Efficient -Cloud-based Data Warehouse -with a Distributed SQL Query Engine that can process terabytes of data in seconds. The traditional way to work with a data warehouse is to start with an ETL job i.e. Extract the raw data from the source, Transform…

We all know how frustrating job hunting can be. The numerous hours spent filling out applications, countless number of rejections and worse yet, recruiters who don’t even acknowledge your existence. …

Learn more about Google’s serverless, highly scalable and lightning fast Data Warehouse here : BigQuery. In this article we will be looking at how to access and query data stored in BigQuery using R and Python. Using R We will be using the bigrquery package created by Hadley Wickham which provides a…