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Items tagged with: dataViz

Climatic analogs for some US urban areas in the late 21st century:
https://www.nature.com/articles/s41467-019-08540-3 @climate

#climateChange #climate #projections #dataViz #map #analog #classification

Contemporary climatic analogs for 540 North American urban areas in the late 21st century - Nature Communications

It is challenging to communicate abstract future climate estimates. Here the authors utilized climate-analog mapping and they identified that North American urban areas’ climate by the 2080’s will become similar to the contemporary climate of locatio…
Nature
#climatechange #Map #dataviz #analog #Climate #projections #classification @Climate - truthful information about climate, related activism and politics.

Neat maps of #AsianFood in the US from Pew Research Center:

https://www.pewresearch.org/short-reads/2023/05/23/71-of-asian-restaurants-in-the-u-s-serve-chinese-japanese-or-thai-food/

via FlowingData newsletter (Nathan Yau) and Pew study authors Sono Shah and Regina Widjaya (none of whom are on Mastodon)

#DataViz #Cartography #maps #visualization

Most Asian restaurants serve Chinese, Japanese or Thai food in the US | Pew Research Center

In the U.S., 12% of all restaurants serve Asian food; that share is slightly higher than the 7% of the U.S. population that is Asian American.
Pew Research Center
#maps #dataviz #cartography #visualization #asianfood

Our paper with Paul Murrell about color palettes in base R is now published in The :rstats: Journal:

Coloring in R's Blind Spot

https://doi.org/10.32614/RJ-2023-071

#rstats #dataviz #color

Screenshot: Coloring in R’s Blind Spot Abstract: Prior to version 4.0.0 R had a poor default color palette (using highly saturated red, green, blue, etc.) and provided very few alternative palettes, most of which also had poor perceptual properties (like the infamous rainbow palette). Starting with version 4.0.0 R gained a new and much improved default palette and, in addition, a selection of more than 100 well-established palettes are now available via the functions palette.colors() and hcl.colors(). The former provides a range of popular qualitative palettes for categorical data while the latter closely approximates many popular sequential and diverging palettes by systematically varying the perceptual hue, chroma, and luminance (HCL) properties in the palette. This paper provides a mix of contributions including an overview of the new color functions and the palettes they provide along with advice about which palettes are appropriate for specific tasks, especially with regard to making them accessible to viewers with color vision deficiencies.
Screenshot Figure 7: New qualitative palettes in base R available from the palette.colors() function. The label above each swatch shows the argument to provide to palette.colors() to produce the set of colors. The palette at top-left is the new default that is also produced by palette(). The "Okabe-Ito" palette is the default that is produced by palette.colors() (with no arguments).
Screenshot Figure 6: Hue, chroma, and luminance paths for the "YlGnBu" (left) and "Viridis" (right) palettes. These plots are created by the colorspace::specplot() function. For "YlGnBu" we can see that hue changes from blue to yellow, luminance increases monotonically, and chroma has a small peak in the blue range and then decreases with luminance. "Viridis", on the other hand, has almost the same trajectory for both hue and luminance, but chroma increases for the light colors.
Screenshot Table 1: An overview of the new palette functionality: For each main type of palette, the Purpose row describes what sort of data the type of palette is appropriate for, the Generate row gives the functions that can be used to generate palettes of that type, the List row names the functions that can be used to list available palettes, and the Robust row identifies two or three good default palettes of that type. Qualitative: Purpose: Categorical data Generate: palette.colors(), hcl.colors() List: palette.pals(), hcl.pals("qualitative") Robust: "Okabe-Ito", "R4" Sequential: Purpose: Ordered or numeric data (high → low) Generate: hcl.colors() List: hcl.pals("sequential") Robust: "Blues 3", "YlGnBu", "Viridis" Diverging: Purpose: Ordered or numeric data with a central value (high ← neutral → low) Generate: hcl.colors() List: hcl.pals("diverging"), hcl.pals("divergingx") Robust: "Purple-Green", "Blue-Red 3"

Coloring in R's Blind Spot

The R Journal
#dataviz #RStats #color

If you just need a pretty figure from a dataset and not the full power of R, have a look at https://data-illustrator.cs.umd.edu/index.php . Data based illustrations without code. #gui #dataviz

Data Illustrator: Create infographics and data visualizations without programming

Create Infographics and Data Visualizations without Programming
data-illustrator.cs.umd.edu
#dataviz #gui

‼️ 1/2 New year, new R package, new rayshader update, new slick Quarto website, new blog post! 5x the new! Introducing the {raybevel} package: generate 3D buildings, 3D beveled polygons, 2D inset polygons, and calculate straight skeletons entirely in R! The rayshader update features tons of improvements, including blazing fast 3D contour and line drawing.

Blog post:
https://www.tylermw.com/posts/rayverse/raybevel-introduction.html

HAPPY NEW YEAR!

#RStats #rayshader #rayrender #raybevel #rayverse #dataviz

Tyler Morgan-Wall - Roofs, Bevels, and Skeletons: Introducing the Raybevel Package

www.tylermw.com
#dataviz #RStats #rayshader #rayrender #rayverse #raybevel

Stop what you're doing and read this heart-breaking essay about Long Covid written by Giorgia Lupi:
https://www.nytimes.com/interactive/2023/12/14/opinion/my-life-with-long-covid.html

It shows how large the impact of this type of disease can be and what it does to the lives of people who suffer from it.

I think this is the most emotionally touching piece of #dataviz / essay / opinion piece I have ever read.

If nothing else, it should inspire you to be kind & helpful to others, esp. if they suffer from any kind of disease, chronic or not.


Opinion | My Life With Long Covid

Chronic illness has a way of picking apart your mind and breaking your heart.
Giorgia Lupi (The New York Times)
#dataviz

#TopologicalDataAnalysis shows how #GeneExpression shaped the form & function of flowering #plants over 125 million years of #evolution, providing a novel way to explore complex biological data. #dataviz @bob_vanburen &co in #PLOSBiology https://plos.io/4actz9N

Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants

Topological Data Analysis shows how gene expression shapes the form and function of flowering plants, which have adapted to dominate Earth’s varied landscapes over 125 million years.
plos.io
#dataviz #plants #plosbiology #evolution #geneexpression #topologicaldataanalysis

Believe it or not, these two charts are showing the same data. The grouped bars chart is from a UN climate report, and the interval bars version is from #TheEconomist. Amazing how much easier the latter is to read with just a few different design choices. #dataviz https://www.economist.com/graphic-detail/2023/11/20/the-world-is-still-failing-to-come-close-to-its-climate-goals
Bar chart of emissions progress for about 20 countries or groups with 2 or three bars per entity.
Chart showing emissions progress as overlapping range bars for each country. One is pledge and one is projection.

The world is (still) failing to come close to its climate goals

Progress has been made. But not nearly enough
The Economist
#dataviz #theeconomist

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