A beautiful sakura tree in full bloom, covered with vibrant pink cherry blossoms. The tree stands alone in a serene park with green grass and a clear blue sky in the background. Soft petals are falling gently to the ground, creating a picturesque and tranquil scene. The sunlight filters through the blossoms, casting a soft glow around the tree. Created with DALL-E.

Sakura Visualizations
Visualizing first and full cherry blossom bloom dates for Japanese regions using R and Python

An old school beige-green Chinese bus and a pair of pliers lying on the ground side by side. The scene is well-lit with a vibrant, clear blue sky overhead and lush green grass underfoot. Created with DALL-E.

Tidy Data Manipulation: dplyr vs siuba
A comparison of R’s dplyr and Python’s siuba data manipulation packages

A squirrel sitting in a bright and friendly office, curiously looking at an old-fashioned rotary dial telephone on a wooden desk. Sunlight filters through the window, creating a warm, welcoming atmosphere. The office is decorated with vibrant green plants in terracotta pots and bookshelves filled with colorful books. Created with DALL-E 3.

Tidy Classification Models: Customer Churn Prediction
A comparison of classification approaches using the tidymodels R package

A cheetah sits beside a computer screen displaying colorful data visualizations and regression models in a bright, welcoming office environment, highlighted by sunlight and decorated with plants and books. Created with DALL-E 3.

Tidy Fixed Effects Regressions: fixest vs pyfixest
A comparison of packages for fast fixed-effects estimation in R and Python

An owl and a peacock are in front of a computer screen displaying a simple bar chart with three colored sections, in a vibrant and welcoming office environment filled with plants and colorful decorations. Created with DALL-E 3.

Tidy Data Visualization: ggplot2 vs matplotlib
A comparison of the two most popular data visualization tools for R and Python

An eagle, a hummingbird, and a butterfly are in front of a computer screen displaying a simple pie chart with three colored sections, in a vibrant and welcoming office environment filled with plants and colorful decorations. Created with DALL-E 3.

Interactive Data Visualization with Python
A comparison of the dynamic visualization libraries plotly, bokeh and altair for the programming language Python

The scene shows a human figure in a friendly and inviting office space, interacting with a simple data visualization on a screen. The office features softer lighting, more vibrant indoor plants, and cozy, colorful furniture that creates a welcoming atmosphere. The large windows let in plenty of natural light, but the overall vibe is relaxed and homelike. The person, smiling and in casual attire, is pointing at a basic, easy-to-understand chart on the screen, making the interaction appear more accessible and less formal. This image emphasizes a comfortable work environment and simplifies the complexity of data analysis. Created with DALL-E 3.

Interactive Data Visualization with R
A comparison of the dynamic visualization packages ggiraph, plotly and highcharter for the programming language R

A server room with a more subdued and professional atmosphere. It features four different database servers, each representing a distinct tabular data storage technology. The first server has a sleek and efficient design, symbolizing a modern, high-performance database. The second server is sturdy and straightforward, indicative of a traditional, reliable database system. The third server is compact and practical, representing an efficient, resource-conserving database. The fourth is advanced yet unobtrusive, suggesting a sophisticated, AI-powered database. The room has soft lighting, with a focus on functionality and neatness. The overall ambiance is more business-like and less flashy, conveying a sense of serious technology at work. Created with DALL-E 3.

Tidy Data: Tabular Data Storage Comparison
A comparison of popular open-source data storage technologies using R and Python

A bright and friendly office setting with two equally sized screens placed centrally on a desk. Each screen displays a simple line chart without any text or numbers. The desk is placed directly on a beach, with no walls or windows, allowing an unobstructed view of the sea and some seagulls in the background. The scene conveys a peaceful and productive atmosphere, with natural beach scenery surrounding the workspace. Created with DALL-E 3.

Tidy Data Visualization: ggplot2 vs seaborn
A comparison of two popular data visualization tools for R and Python

An image of a bright and friendly office setting with two equally sized screens placed centrally. Each screen displays a simple line chart without any text or numbers. The office is very well-lit, giving a warm and inviting ambiance. The decor is colorful and cheerful, with a minimalist design. The two screens are on a sleek, modern desk in the center of the image. The line charts are clear and straightforward. The overall atmosphere of the office is lively and welcoming, with vibrant colors and ample natural light. Created with DALL-E 3.

Tidy Data Visualization: ggplot2 vs plotnine
A comparison of implementations of the grammar of graphics in R and Python.

A standard plastic broom stands upright on a lush green lawn, with its long handle and bristles clearly visible. Beside it is a large pair of pliers, about half the size of the broom, with detailed rubber handles. The background shows a serene landscape, with a sparkling lake visible in the distance, surrounded by gentle hills and a clear blue sky. Created with DALL-E 3.

Tidy Data Manipulation: dplyr vs TidierData
A comparison of R’s dplyr and Julia’s TidierData data manipulation packages

A panda bear sitting calmly in a green bamboo forest. The panda has a curious expression as it looks at a red-handled plier placed on the ground in front of it. The plier is shiny and contrasts with the natural, lush environment. The background is filled with thick bamboo stalks and a variety of green plants, enhancing the natural habitat of the panda. The scene is peaceful, with soft, natural lighting highlighting the panda and the plier. Created with DALL-E 3.

Tidy Data Manipulation: dplyr vs pandas
A comparison of R’s dplyr and Python’s pandas data manipulation packages

An ibis bird, with its long, curved beak and distinctive white plumage, standing in a brightly lit environment. The bird is curiously looking at a single pair of shiny, metallic pliers lying on the ground. The surroundings are vibrant and well-lit, with a clear blue sky overhead and lush green grass underfoot. The scene captures a sense of curiosity and contrast between the natural bird and the man-made tool. Created with DALL-E 3.

Tidy Data Manipulation: dplyr vs ibis
A comparison of R’s dplyr and Python’s ibis data manipulation packages

A realistic polar bear sitting on a snowy landscape, looking curiously at a pair of pliers lying on the ground. The polar bear should have a thick, white coat and appear both majestic and inquisitive. The pliers are standard steel with red rubber grips, contrasting against the white snow. The scene is set in the Arctic with a clear blue sky and a few distant icebergs in the background. Created with DALL-E 3.

Tidy Data Manipulation: dplyr vs polars
A comparison of R’s dplyr and Python’s polars data manipulation packages

Analyzing Seasonality in DAX Returns
Debunking the Halloween indicator for German market returns using R

Scraping ESG Data from Yahoo Finance
How to scrape environmental, social and governance risk scores using R

Clustering Binary Data
An application of different unsupervised learning approaches to cluster simulated survey responses using R

Tidy Data: A Recipe for Efficient Data Analysis
On the importance of tidy data for efficient analysis using the analogy of a well-organized kitchen

A 3d rendered image of two stylized AI robots sitting at a round table, immersed in a discussion with a large, abstract, holographic projection of a collaborative filtering algorithm matrix in the middle. Created with DALL-E 3.

Tidy Collaborative Filtering: Building A Stock Recommender
A simple implementation for prototyping multiple collaborative filtering algorithms using R
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