The Iris Species Explorer presentation provides an interactive overview of the classic Iris dataset, which is widely used in machine learning and statistics for classification tasks. The dataset contains measurements of sepal length, sepal width, petal length, and petal width for 150 iris flowers belonging to three species: Setosa, Versicolor, and Virginica. This presentation includes: A summary of the dataset’s structure and species distribution. Visualizations such as boxplots comparing sepal and petal lengths across species. A scatter plot exploring the relationship between petal length and sepal length, color-coded by species. The goal is to help users understand key differences between iris species through clear data summaries and graphical insights.

The Iris Species Explorer presentation provides an interactive overview of the classic Iris dataset, which is widely used in machine learning and statistics for classification tasks. The dataset contains measurements of sepal length, sepal width, petal length, and petal width for 150 iris flowers belonging to three species: Setosa, Versicolor, and Virginica. This presentation includes: A summary of the dataset’s structure and species distribution. Visualizations such as boxplots comparing sepal and petal lengths across species. A scatter plot exploring the relationship between petal length and sepal length, color-coded by species. The goal is to help users understand key differences between iris species through clear data summaries and graphical insights.

So far, the contents are from StatQuest

Analyzing a dataset that I found in kaggle

Riesgo de crédito.

This analysis examined teacher feedback from Marymount International School Rome collected in January and June 2025, exploring priorities for enhancements to the school’s data dashboard. By merging cleaned survey data from both collection periods (39 teacher responses across ECC, Elementary, and Secondary), the study identified the most frequently requested features. Thematic and text analyses revealed strong demand for progress tracking tools and grade-level comparisons, alongside interest in behavior and attendance monitoring, assessment clarity, and individualized insights. Visualizations—including top word counts, thematic bar charts, and word clouds by division—highlight the distinct needs across school sections, supporting the development of a more dynamic and responsive dashboard for holistic student data.

Neste artigo, adotamos o método manual para realizar a análise de componentes principais.