Use Cramer’s V test to check how strongly associated are two categorical variables — Introduction Feature selection is an important step for any data science project. …

Try these codes if you want to make your Python code cleaner and more readable. — I usually work with Python and R languages on my daily job. All of that “what’s the best programming language” rivalry aside, I like them both. …

A complete toolbox for those small tasks that we keep forgetting how to program. I work as a Data Scientist and I am constantly in contact — working or learning — with the latest technologies in the field. However, let me tell you something: I still like the good old…

Sneak peek into my new book released in February. A little of my history If you follow my Linkedin page, you may already be aware that I am about to release a book called Data Wrangling with R with Packt Publishing. The issuing date is February 23, 2023. So, it’s already available in Amazon and…

Gain more knowledge in regexp with stringR — Introduction When a project involves text analysis, such as sentiment analysis, text mining, or any other task you were entitled to do analyzing textual information will probably require parsing text at some point. This mean that one will have to extract a piece of a text or find a given pattern…

Aprenda os passos básicos para rodar uma AnaCor no R. — Introdução Datasets são feitos de números e/ou texto. Logo, espera-se que nem todas as variáveis sejam apenas números, os quais, por sua vez, contam com muitas técnicas para serem analisados, testados e trabalhados. Quando estamos trabalhando com variáveis numéricas, existem ferramentas como correlação, PCA, escala, normalização e vários testes disponíveis. Por…

Learn the basic steps to run a Multiple Correspondence Analysis in R — Introduction Datasets are made of numbers and/ or text. Thus, we should expect that not all the variables will be just about numbers, which, by the way, count on many techniques to be analyzed, tested and worked. When we are working with numerical variables, there are tools like correlation, PCA, scaling…

It is easy to return more than a Boolean list. When you’re using Scikit Learn’s SelectKBest, you are interested in returning the k best features for you model. …

Tweak your model to classify only with a higher degree of certainty — Introduction When creating a classification model, many algorithms offer the function predict_proba() to give us the probability of that observation being classified under each class. Thus, it is common to see an output like this: [0.925, 0.075] In the previous case, the model is 92.5% sure that the observation pertains to…