Data Preprocessing for Machine Learning Models

Data Preprocessing for Machine Learning Models
Data preprocessing ensures that the data is ready for analysis, improves the efficiency of subsequent tasks, and contributes to the overall success of data-driven projects. What is the Purpose of Data Preprocessing? So, what is the big deal about preprocessing our data? Well to start, data preprocessing allows for a…

Creating Python Dashboard using Dash

Creating Python Dashboard using Dash
Check out other post about the dashboard Getting data from US BLS open data using BLS API key Getting data from US EIA website using EIA API key Python Dashboard available here Full Code available on GitHub Building the New Layout For the new layout of the dashboard, I wanted…

Using EIA API to Extract Data from the US EIA Website

Using EIA API to Extract Data from the US EIA Website
The EIA API allows user to connect and import historical publicly available data from the EIA website. There are many data regarding oil prices, utility prices, oil production rates, oil consumption rates, etc. This post is gathering data using the EIA API, and we will explore gathering data through the US EIA website using an API key.

Using API to Extract Data from the US BLS Website

Using API to Extract Data from the US BLS Website
Users can access a wealth of historical data on numerous economic indicators, such as food, oil, utility prices, CPI values, and more, through the US BLS API. The BLS API is a useful tool for obtaining freely accessible data, which can then be used for analysis or development. It provides a practical and effective way to access and use the data provided by the Bureau of Labor Statistics, allowing users to conduct studies, analyze trends, and create applications based on accurate economic data.

Analyzing Smart Device Usage: Bellabeat Case Study

Analyzing Smart Device Usage: Bellabeat Case Study
This is the Bellabeat case study project from the Google Data Analytics Specialization, and the goal of this case study is to demonstrate the process of Ask, Prepare, Process, Analyze, Share, Act. These 8 processes are very important for doing data analysis, they ensure we get consistent, repeatable processes each time.