lidR
ggplot2
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lidR | ggplot2 | |
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5 | 62 | |
557 | 6,328 | |
3.9% | 1.2% | |
7.7 | 9.4 | |
23 days ago | 1 day ago | |
R | R | |
GNU General Public License v3.0 only | 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.
lidR
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DSM Los Angeles
Hey all :) I am currently computing a DSM for Los Angeles (~10600 km²) based on the 2015 - 2016 LARIAC Lidar data (it's part of NOAA). So far they provide the raw LiDAR data, a DEM at 3ft resolution and building heights polygons based on their LiDAR data. However, since I need a DSM for a hobby project, I am currently computing one with the lidR R package. It's at 3 ft resolution to match it with the DEM. I am definitely no pro at this kind of work but from a first glance the results look good.
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[HELP] Converting LAZ to LAS so I can generate a DEM in ArcMap.
If you use R, there are many tools for not only converting point cloud types, but also creating DEM/DSM, feature detection, and more. Check out the lidR package! LasTools also does this (and does it VERY well) but the unrestricted tools that preserve the data quality cost $$. I actually do like the way they set up LasTools pricing though - it’s simple and only a few grand. But nothing beats free!
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New to GIS
People here are going to focus on Python, but I cannot recommend using the R programming language as a GIS enough. There is an amazing library for working with lidar data called lidR that I think would be worthwhile. Also, the r4ds book is another great starting point for learning R for data analysis and general programming.
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lidR voxel_metrics : total number of points per x-y voxel/rectangle summed along axis z?
And this seemed promising, but I didn't understand how `~length(Z)` behaves. Based on the example https://github.com/Jean-Romain/lidR/blob/4612963e6f73ead5840715434f55eaa46ec5ce24/R/voxel_metrics.R#L67
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LiDAR derived DSM - power line "artefact"
It's my first time working with LiDAR data. I am using the R package lidR.
ggplot2
- ggplot2
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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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Relative frequency of letters in five-letter English words (Wordle aid) [OC]
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.
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[OC] U.S. News & World Report Best Colleges: 2002 to 2023
Thanks, it's an interesting idea! I definitely could implement this with scale_fill_gradientn) in ggplot2.
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Facts about Aaron Boone's Ejections as Manager
I used the ggplot2 package in R to create these figures.
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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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[OC] Visualizing Financial Market Returns Across Many Asset Classes via Heatmaps
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.
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[OC] Forbes List of Highest-Earning Musicians: 1987 to 2021
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).
What are some alternatives?
esquisse - RStudio add-in to make plots interactively with ggplot2
Altair - Declarative statistical visualization library for Python
rmarkdown - Dynamic Documents for R
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
glue - Glue strings to data in R. Small, fast, dependency free interpreted string literals.
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.
mirt - Multidimensional item response theory
her-majesty-php - Britanised edition of PHP
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.