For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / 9 months ago
I got the list of five-letter words from the words package in R, created the QWERTY keyboard grid with base R and tibble, and visualized the data with geom_tile in the ggplot2 package. Source: 10 months ago
Thanks, it's an interesting idea! I definitely could implement this with scale_fill_gradientn) in ggplot2. Source: 11 months ago
I used the ggplot2 package in R to create these figures. Source: 11 months ago
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... - Source: dev.to / 11 months ago
Sorry about the slow reply, but the auto-moderator seems to be deleting my comments (for some unknown reason). I will try once more: the geom_tile function in ggplot2. Source: 11 months ago
Visual cues are a much better idea, thanks! Unfortunately, I don't know how to do that in ggplot2, either (I created these figures in R). Source: 11 months ago
This should get you started. Here's another good cheat sheet. Ggplot2 is pretty logical once you get the jist. Putting the legend on the right side is absolutely possible. Source: 12 months ago
I highly suggest checking out some ggplot resources online, such as this documentation. I understand that you're getting your desired plots, but your syntax is a little wonky. Source: 12 months ago
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... Source: 12 months ago
For more information on how to use ggplot2 and create charts consult the ggplot2 official page or the ggplot2 cheat graphic. - Source: dev.to / about 1 year ago
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