Search Results for "visualization"
Sort By:
Showing 10 open source projects for "visualization"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
-
1
Awesome Network Analysis
A curated list of awesome network analysis resources
awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data. -
2
NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
The nyc-taxi-data repository is a rich dataset and exploratory project around New York City taxi trip records. It collects and preprocesses large-scale trip datasets (fares, pickup/dropoff, timestamps, locations, passenger counts) to enable data analysis, modeling, and visualization efforts. The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of pickups/dropoffs). It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. ... -
3
plotly
An interactive graphing library for R
This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of... -
4
easystats
The R easystats-project
easystats is a meta‑package that installs and unifies a suite of R packages for post‑processing statistical models. It delivers a consistent API to assess model performance, effect sizes, parameters, and to generate reports and visualizations, all with minimal dependencies and maximum clarity. -
The Most Powerful Software Platform for EHSQ and ESG ManagementChoose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
-
5
RStudio Cheatsheets
Curated collection of official cheat sheets for data science tools
...The repository contains source files (R Markdown or LaTeX) that generate the cheat sheets, version history, and metadata (title, author, description) for each. It covers topics such as data wrangling, data import, modeling, visualization, RStudio IDE shortcuts, Shiny development, and the tidyverse suite (dplyr, ggplot2, tidyr, purrr). These cheat sheets are widely used by R learners, educators, and practitioners as quick reference tools, and they often ship with RStudio by default or are linked from RStudio’s help/documentation pages. Users can also contribute new cheat sheet proposals, corrections, or translations via pull requests. -
6
MetBrewer
Color palette package inspired by Metropolitan Museum of Art in NY
MetBrewer is an R package that provides color palettes inspired by artworks and collections in the Metropolitan Museum of Art (The Met). The idea is to draw on the rich visual heritage of fine art to generate palettes that are aesthetically pleasing and grounded in real-world artistic color usage. The palettes are curated, named after artworks or styles, and often include notes about colorblind-friendliness and contrast. The package supports both discrete and continuous palette types, with... -
7
R Color Palettes
Comprehensive list of color palettes available in R
This repository is a curated collection of color palettes crafted or curated for data visualization in R. The goal is to provide designers, data scientists, and R users with aesthetically pleasing, perceptually consistent color schemes that work well for plots, maps, and graphics. The repo contains static files listing palette definitions (e.g. hex codes, named hues), sample visualizations showing how each palette performs under different contexts (categorical, sequential, diverging), and helper functions/scripts to import or use the palettes in R. ... -
8
ggthemes
Additional themes, scales, and geoms for ggplot2
ggthemes is an R package that provides extra themes, scales, and geoms for ggplot2. It supplements the default ggplot2 offerings by allowing users to apply special themes (e.g., inspired by classic publications, external visualization styles), additional scale functions, and specialized geoms or color scales. It is often used to make ggplot2 plots adhere to aesthetic styles from famous news outlets, scientific journals, or presentation decks. Additional color scales and palettes for discrete and continuous data to match theme aesthetics. Extensive documentation and examples for each theme / scale so users can see how plots look and tweak them. -
9
DataScienceR
a curated list of R tutorials for Data Science, NLP
...It includes an assortment of exercises, sample datasets, and instructional code that cover the core steps of a data science project: data ingestion, cleaning, exploratory analysis, modeling, evaluation, and visualization. Many of the modules demonstrate best practices in R, such as using the tidyverse, R Markdown, modular scripting, and reproducible workflows. The repository also shows examples of linking R with external resources — APIs, databases, and file formats — and integrating into larger pipelines. It acts as a learning scaffold for students or beginners transitioning to more advanced data science work in R, offering a hands-on, example-driven approach. ... -
Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
-
10
Investing
Investing Returns on the Market as a Whole
This repository, owned by the user zonination (Zoni Nation), presents a data visualization and analysis project on long-term returns from broad stock market indexes, especially the S&P 500. The author gathers historical price data (adjusted for inflation and dividends) and computes growth trajectories under a “buy and hold” strategy over decades. The key insight illustrated is that over sufficiently long holding periods (e.g. 40 years), the stock market stabilizes and nearly always yields positive returns, even accounting for extreme market crashes and recessions. ...
- Previous
- You're on page 1
- Next
