Multiplex: visualizations that tell stories—A Python library to create and annotate beautiful network graph visualizations, text visualizations and more.
As our examples grow they becomes a bit harder to navigate. Might be good to think about organizing them better. Maybe a (max 1 layer deep) dir structure, or just more sensible names.
Related, I really like how the Threejs examples can be searched by keyword. Maybe something for our docs? (Technically a separate issue.)
A collection of geoms for R's 'ggplot2' library. geom_shadowpath(), geom_shadowline(), geom_shadowstep() and geom_shadowpoint() functions draw a shadow below lines to make busy plots more aesthetically pleasing. geom_glowpath(), geom_glowline(), geom_glowstep() and geom_glowpoint() add a neon glow around lines to get a steampunk style.
It is well known that the stock market exhibits very high dimensionality due to the almost unlimited number of factors that can affect it which makes it very difficult to predict. Studying how global stock market indexes respond to headlines can provide a major advantage in predicting stock movements and making trade decisions. Naturally, fundamental and technical indicators are not to be neglected and the goal of the project is to combine all of these aspects to achieve a model that thinks as an experienced trader.
The purpose of this project is to process the dataset, analyze it, do some feature engineering and finally make a predictive loan model for an applicant.
As our examples grow they becomes a bit harder to navigate. Might be good to think about organizing them better. Maybe a (max 1 layer deep) dir structure, or just more sensible names.
Related, I really like how the Threejs examples can be searched by keyword. Maybe something for our docs? (Technically a separate issue.)