What a yarn! Journalists are turning to #crochet to tell data stories
“I’m really interested in these beautiful, touchable representations of data that use texture to encode information in a way that our screens cannot reproduce.”
Check out Dr. Albert Rapp's latest YouTube video on mastering the great_tables Python package! From raw data to polished displays, learn about custom fonts, nanoplots, conditional formatting, and the steps to great a lovely looking data display table with great_tables. https://www.youtube.com/watch?v=ESyWcOFuMQc&ab_channel=AlbertRapp
#KDE will mentor ten projects in Google Summer of Code (#GSoC) this year, including two projects for #LabPlot, a FREE, open source and cross-platform #DataVisualization and #DataAnalysis software.
This is an excellent story by alvin chang about the impact of adverse childhood experiences.
After introducing the main character, Alex, the simulation has both a marker and an animation delay to help you keep track of the him throughout the story.
The Learn R Through Examples by Xijin Ge, Jianli Qi, and Rong Fan provides an introduction to data analysis with R. The book covers the core topics of data analysis using different datasets, from simple and clean datasets to messy and big datasets. 🧵👇🏼
Well it's that time of week again, a new episode of WHG is now live! This week @thebimsider and our series guest host @johntpierson have a fun conversation with @jisell Howe, CDT about Sketchnotes, DIY Websites, Data Storytelling, Coding, Speaker Trading Cards? (Carl almost didn't let John ask about these, stay to the end to find out what its all about 😁)
and lots more!
You can have a listen on your favorite podcast app, or the link below 👇
The R Workflow by Prof. Frank E Harrell Jr is a new book (WIP) that focuses on reproducible data analysis and reporting with R. That includes the following topics:
✅ Data processing
✅ Descriptive analysis
✅ Data visualization
✅ Reporting
The Complex Analysis book by Juan Carlos Ponce Campuzano focuses on the theory and applications of complex functions. The book makes great use of interactive data visualizations to explain the complex analysis theory.
𝗗𝘂 𝗕𝗼𝗶𝘀 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗦𝗼𝗰𝗶𝗲𝘁𝘆 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 - 𝗪𝗲𝗲𝗸 𝟵/𝟭𝟬. My re-creation of Du Bois' poster no. 51 implemented with D3 & Svelte. Once more close to the original and responsive.
I came across this awesome Python - itables (Interactive Tables), a Python wrapper for the DataTable JS library ❤️. The package displays Pandas 🐼 and Polars 🐻❄️ tables in Jupyter Notebooks as interactive HTML widgets, enabling the user to sort, paginate, score, or filter the data.
(1/2)Statistical Inference via Data Science - New Edition 📚👇🏼
The Statistical Inference via Data Science by Chester Ismay and Prof. Albert Y. Kim recently released a new edition. This book focuses on the data analysis workflow and how to answer questions with data. This includes the following topics:
✅ Data wrangling
✅ Data visualization
✅ Simple and multivariate regression analysis
✅ Sampling and bootstrap
✅ Hypothesis testing
Day One of our cozy @ieeevis writing retreat has kicked off at the Northeastern Roux Institute campus in Portland Maine! Excited to see what folks submit this year 😍
Makie is a data visualization ecosystem for the Julia programming language, with high performance and extensibility. It supports various data visualization applications like 2D, 3D, and geospatial plots.
Feeling stuck with Excel for data analysis? You're not alone! Excel is fantastic, but for truly powerful insights and visualizations, it can fall short.
Here's what you'll gain:
🧐 * Advanced data manipulation & cleaning
💻 * Powerful statistical analysis & modeling
📉 * Eye-catching data visualizations
🌟 * Seamless integration back to Excel
(1/2) Data Analysis for Social Scientists - MIT Course 🚀
MIT released a new course - Data Analysis for Social Scientists (MIT 14.310x), focusing on data analysis for social fields of science such as economics, public policy, and culture. This ten weeks course, by Prof. Esther Duflo and Dr. Sara Ellison, covers topics such as:
(2/2) This ten weeks course, by Prof. Esther Duflo and Dr. Sara Ellison, covers topics such as:
✅ Probability and Statistics
✅ Regression analysis
✅ Design of experiments
✅ Randomized control trails and A/B testing
✅ Machine learning
✅ Data visualization