Unusual method implementations to control attributes — Primer We can take advantage of magic methods in Python to control attributes that are being set. In this tutorial guide, I present 3 methods using the call, setattr, and a decorator for the init method as unique ways to control how attributes can be set. As a caveat, the code…

An Example Led Guide — Attribute validation ensures user submitted data is in the correct format or type. Attribute control in Python can be control in many ways. Here I present two unusual, but interesting ways to control attributes. Example 1: Using the magic call method for attribute re-assignment To begin this example, I first create a class called Employees, which has three attributes, name…

Custom messages during the log in and log out process in Flask — When a user logs in to a web application, a personal display message can set the tone for a warm welcome. In Flask, displaying a welcome message to the user can be achieved in many ways. …

Wrangle your raw dataset to produce an Animated Bar Plot — Plotting Antibiotic prescribing rates in US counties This tutorial details how to transform raw data into an animated barplot using the Plotly library in Python. The dataset used in this tutorial is titled: ‘Potentially Avoidable Antibiotic Prescribing observed and risk-adjusted rates for child Medicaid enrollees by provider county beginning in 2010’.

Producing Informative Geopandas plots — Introduction Antibiotic resistance is being increasingly detected in bacteria. Of concern, is the rise in resistance towards antibiotics of last-resort. In this tutorial, I demonstrate how the Geopandas library in Python can be used as a tool to draw attention to antibiotic resistance globally. …

Exert Control over the attributes in your Class — Control your attributes This tutorial will demonstrate how to simply create read-only and deletion proof attributes in your Python class. In this way, an extra layer of control can be applied to your attributes, ensuring that your class is being used as intended. …

Simply use SimpleImputer — Missing Value Imputation Datasets often have missing values and this can cause problems for machine learning algorithms. It is considered good practise to identify and replace missing values in each column of your dateset prior to performing predictive modelling. This method of missing data replacement is referred to as data imputation. Missing values…

Introductory guide to K-Nearest Neighbors via a code example — K-Nearest Neighbors (KNN) KNN is a supervised machine learning algorithm that can be used to solve both classification and regression problems. The principal of KNN is the value or class of a data point is determined by the data points around this value. To understand the KNN classification algorithm it is often best…

Best Data Scraping Practices using selenium in Python — Selenium for web scraping Selenium is a browser automation library. Most often used for testing web-applications, Selenium may be used for any task that requires automating interaction with the browser. This can include web-scraping. The following tutorial will be a user-led guide of best practices for web-scraping using selenium. I have listed my 5…