datapasta
ggplot2
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datapasta | ggplot2 | |
---|---|---|
3 | 62 | |
881 | 6,292 | |
- | 1.4% | |
0.0 | 9.4 | |
almost 2 years ago | 7 days ago | |
R | R | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
datapasta
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Tracking mentions began in Dec 2020.
ggplot2
- Ask HN: How do you build diagrams for the web?
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Visualizing shapefiles in R with sf and ggplot2!
ggplot2
- Ask HN: What plotting tools should I invest in learning?
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Fueling Innovation and Collaborative Storytelling
This might not be at the top of your list, but science fiction often presents advanced data analysis and visualization technologies. Open source data analysis tools such as Python's Pandas and R's ggplot2 have revolutionized the field, making complex data manipulation and visualization accessible to all. In the science fiction novel The Martian, astronaut Mark Watney uses a variety of data analysis and visualization tools to survive on Mars. He uses Python's Pandas to clean and organize data, and he uses R's ggplot2 to create visualizations of his data. These tools allow him to make sense of the vast amounts of data and help him to make critical decisions about his survival.
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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JSON to PDF Magic: Harnessing LaTeX and JSON for Effortless Customization and Dynamic PDF Generation
For more information on how to use ggplot2 and create charts consult the ggplot2 official page or the ggplot2 cheat graphic.
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osdc-2023-assignment1
ggplot2 (I wish I used more) (https://ggplot2.tidyverse.org/)
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Results of "Neovim built-in options survey" (more in comments)
R and ggplot2 (and tidyverse in general). Here is the code (towards end of file).
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People who live near other people vote for Democrats
Tools used: various packages in R (tidycensus, dplyr, ggplot2, sf)
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isoband - CRAN is having a leftpad moment.
Except it’s not a left pad moment. The isoband maintainer has been alerted in advance and the problem is already fixed, ready to be pushed next week.
What are some alternatives?
Altair - Declarative statistical visualization library for Python
tmap - R package for thematic maps
vega - A visualization grammar.
dplyr - dplyr: A grammar of data manipulation
worldfootballR - A wrapper for extracting world football (soccer) data from FBref, Transfermark, Understat and fotmob
deneb - Deneb is a custom visual for Microsoft Power BI, which allows developers to use the declarative JSON syntax of the Vega or Vega-Lite languages to create their own data visualizations.
glue - Glue strings to data in R. Small, fast, dependency free interpreted string literals.
mirt - Multidimensional item response theory
ggshadow - 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.
her-majesty-php - Britanised edition of PHP
fontawesome - Easily insert FontAwesome icons into R Markdown docs and Shiny apps
postcss-spiffing - PostCSS plugin to use British English