GHTorrent applies AI to data analysis, extraction, visualization, or business intelligence.
Highcharter is an R wrapper for the Highcharts JavaScript charting library and its modules, delivered through an htmlwidget. The hchart(x) function charts data frames, vectors, ts, xts, forecast and survfit objects. It supports Highstock candlestick charts, Highmaps choropleth charts, themes, and plugins. Highcharts offers a commercial license and a free non-commercial license; the package does not provide a Highcharts license.
ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. Users provide the data and specify how variables map to aesthetics and which graphical primitives to use, and the system handles the details. It is described as over 10 years old, and installation is available through the tidyverse or as a standalone package.
The Data Science Lab is a blog of experiments with data. Posts cover topics including k-means clustering, k-means++ seeding, the gap statistic, and an alternative approach to selecting the optimal number of clusters based on a 2004 publication by Pham, Dimov and Nguyen. A 2014 annual report notes the blog was viewed about 74,000 times that year.
dygraphs is a fast, flexible open source JavaScript charting library that allows users to explore and interpret dense data sets. Charts are interactive, with zoom, pan and mouseover available by default, and the library handles very large data sets. It works in all recent browsers.
Astropy is a community effort to develop a common core package for astronomy in Python and foster an ecosystem of Affiliated Packages. Installation is available via pip and other package managers, and the project provides tutorials, documentation, and community help channels.
dplyr is an R package providing a grammar of data manipulation with a consistent set of verbs, including mutate(), select(), filter(), summarise() and arrange(), which combine with group_by(). It is designed to abstract over how data is stored, so the same R code works with local data frames and remote database tables via the dbplyr package.
Community notes
Be the first to share how this project worked for you.
Sign in with a verified account to leave a review or join the discussion.
Sign in to reviewKeep exploring
Highcharter is an R wrapper for the Highcharts JavaScript charting library and its modules, delivered through an htmlwidget. The hchart(x) function charts data frames, vectors, ts, xts, forecast and survfit objects. It supports Highstock candlestick charts, Highmaps choropleth charts, themes, and plugins. Highcharts offers a commercial license and a free non-commercial license; the package does not provide a Highcharts license.
ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. Users provide the data and specify how variables map to aesthetics and which graphical primitives to use, and the system handles the details. It is described as over 10 years old, and installation is available through the tidyverse or as a standalone package.
The Data Science Lab is a blog of experiments with data. Posts cover topics including k-means clustering, k-means++ seeding, the gap statistic, and an alternative approach to selecting the optimal number of clusters based on a 2004 publication by Pham, Dimov and Nguyen. A 2014 annual report notes the blog was viewed about 74,000 times that year.
dygraphs is a fast, flexible open source JavaScript charting library that allows users to explore and interpret dense data sets. Charts are interactive, with zoom, pan and mouseover available by default, and the library handles very large data sets. It works in all recent browsers.
Astropy is a community effort to develop a common core package for astronomy in Python and foster an ecosystem of Affiliated Packages. Installation is available via pip and other package managers, and the project provides tutorials, documentation, and community help channels.
dplyr is an R package providing a grammar of data manipulation with a consistent set of verbs, including mutate(), select(), filter(), summarise() and arrange(), which combine with group_by(). It is designed to abstract over how data is stored, so the same R code works with local data frames and remote database tables via the dbplyr package.
