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GitHub - mtennekes/tmap: R package for thematic mapsR package for thematic maps. Contribute to mtennekes/tmap development by creating an account on GitHub.
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GitHub - mtennekes/tmap: R package for thematic maps
tmap: thematic maps in R
tmap is an actively maintained open-source R-library for drawing thematic maps. The API is based on A Layered Grammar of Graphics and resembles the syntax of ggplot2, a popular R-library for drawing charts.
See below the source code for these images.
Installation
tmap is available on . Installation is straightforward:
install.packages("tmap")
For Linux and macOS users who are new to working with spatial data in R, this may fail since additional (non-R) libraries are required (which are automatically installed for Windows users).
Windows No additional installation required.
Linux (Ubuntu) See https://geocompr.github.io/post/2020/installing-r-spatial-ubuntu/. Please address installation issues in this issue.
macOS See http://www.kyngchaos.com. Please address installation issues in this issue.
Development
The latest development version can be installed using devtools.
In order to use the development version of tmap, it is recommended to use the development version of tmaptools as well:
library(remotes)
install_github("r-tmap/tmaptools")
install_github("r-tmap/tmap")
See NEWS for the latest features and improvements and the issue list for discussions of enhancements and bugs.
Do you want to help with the development of the package? Please let us know! Any feedback, requests, tips, or bug reports are welcome!
Usage
library(tmap)
Book
Tennekes, M., Nowosad, J., Elegant and informative maps with tmap. Draft version, https://r-tmap.github.io/
Reference
Tennekes, M., 2018, tmap: Thematic Maps in R, Journal of Statistical Software, 84(6), 1-39
This paper has been written for tmap 1.11-2. See the reproducible code using tmap 2.x and 3.x.
Vignettes
tmap: what is changed in recent versions?
Tutorials
Presentations
- Creating thematic maps in R (OpenGeoHUB Summer School 2019)
- Plotting spatial data with R (eRum 2018)
- Exploring and presenting maps with tmap (useR!2017)
- tmap: creating thematic maps in a flexible way (useR!2015)]
Other resources
- Geocomputation with R; Making maps with R, Robin Lovelace, Jakub Nowosad, Jannes Muenchow
- R tip: Create maps in R
- Working with Spatial Data and using tmap, Samantha A. Alger
- Computer World: Mapping in R just got a whole lot easier
- National Socio-Environmental Synthesis Center: Maps in R
- Introduction to visualising spatial data in R
- Blog post StatialControl
- Blog post TWIAV
- Computer World: Create maps in R in 10 (fairly) easy steps
- Computer World: Great R packages for data import, wrangling and visualization
- Tutorial Visualising spatial data: from base to shiny - workshop
- Stack Overflow questions (#tmap)
Getting help
There are two main places to get help with tmap:
- stackoverflow is a great source of answers to common tmap questions. It is also a great place to get help, once you have created a reproducible example that illustrates your problem. Please tag your questions with tmap.
- If you have a request or if think your problem is caused by a bug, please open an issue, preferably with a reproducible example.
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https://github.com/hadley/tidyverseEasily install and load packages from the tidyverse - tidyverse/tidyverse - 128:no_entry: ARCHIVED Accesses the Monkeylearn API for Text Classifiers and Extractors
https://github.com/masalmon/monkeylearn:no_entry: ARCHIVED :no_entry: Accesses the Monkeylearn API for Text Classifiers and Extractors - GitHub - ropensci-archive/monkeylearn: :no_entry: ARCHIVED Accesses the Monkeylearn API for Text Cl... - 129:christmas_tree:Visualization and annotation of phylogenetic trees
https://github.com/GuangchuangYu/ggtree:christmas_tree:Visualization and annotation of phylogenetic trees - YuLab-SMU/ggtree - 130Read SPSS, Stata and SAS files from R
https://github.com/hadley/havenRead SPSS, Stata and SAS files from R. Contribute to tidyverse/haven development by creating an account on GitHub. - 131RPy (R from Python)
http://rpy.sourceforge.net/Download RPy (R from Python) for free. RPy is a very simple, yet robust, Python interface to the R Programming Language. It can manage all kinds of R objects and can execute arbitrary R functions (including the graphic functions). - 132Fast and Simple MongoDB Client for R
https://github.com/jeroenooms/mongoliteFast and Simple MongoDB Client for R. Contribute to jeroen/mongolite development by creating an account on GitHub. - 133An implementation of the Grammar of Graphics in R
https://github.com/hadley/ggplot2An implementation of the Grammar of Graphics in R. Contribute to tidyverse/ggplot2 development by creating an account on GitHub. - 134An interactive graphing library for R
https://github.com/ropensci/plotlyAn interactive graphing library for R. Contribute to plotly/plotly.R development by creating an account on GitHub. - 135Simple web scraping for R
https://github.com/hadley/rvestSimple web scraping for R. Contribute to tidyverse/rvest development by creating an account on GitHub. - 136dplyr: A grammar of data manipulation
https://github.com/hadley/dplyrdplyr: A grammar of data manipulation. Contribute to tidyverse/dplyr development by creating an account on GitHub. - 137A database interface (DBI) definition for communication between R and RDBMSs
https://github.com/rstats-db/DBIA database interface (DBI) definition for communication between R and RDBMSs - r-dbi/DBI - 138๐ A Swiss-Army Knife for Data I/O
https://github.com/leeper/rio๐ A Swiss-Army Knife for Data I/O. Contribute to gesistsa/rio development by creating an account on GitHub. - 139Read flat files (csv, tsv, fwf) into R
https://github.com/hadley/readrRead flat files (csv, tsv, fwf) into R. Contribute to tidyverse/readr development by creating an account on GitHub. - 140An R package for the Quantitative Analysis of Textual Data
https://github.com/kbenoit/quantedaAn R package for the Quantitative Analysis of Textual Data - quanteda/quanteda - 141Fast reading of delimited files
https://github.com/r-lib/vroomFast reading of delimited files. Contribute to tidyverse/vroom development by creating an account on GitHub. - 142Posit
http://www.rstudio.org/The best data science is open source. Posit is committed to creating incredible open-source tools for individuals, teams, and enterprises. - 143rocker-org
https://github.com/rocker-orgrocker-org has 27 repositories available. Follow their code on GitHub. - 144rOpenHealth
https://github.com/rOpenHealthA collaborative project to build R tools facilitating access to quantitative healthcare and public health data - rOpenHealth - 145a fast interpreter and JIT for R
https://github.com/jtalbot/ripostea fast interpreter and JIT for R. Contribute to jtalbot/riposte development by creating an account on GitHub. - 146Visualise line profiling results in R
https://github.com/hadley/lineprofVisualise line profiling results in R. Contribute to hadley/lineprof development by creating an account on GitHub. - 147Functions for installing softwares from within R
https://github.com/talgalili/installr/Functions for installing softwares from within R. Contribute to talgalili/installr development by creating an account on GitHub. - 148A logging package in R similar to log4j
https://github.com/zatonovo/futile.loggerA logging package in R similar to log4j. Contribute to zatonovo/futile.logger development by creating an account on GitHub. - 149Mixed-effects models in R using S4 classes and methods with RcppEigen
https://github.com/lme4/lme4Mixed-effects models in R using S4 classes and methods with RcppEigen - lme4/lme4 - 150Create Blogs and Websites with R Markdown
https://github.com/rstudio/blogdownCreate Blogs and Websites with R Markdown. Contribute to rstudio/blogdown development by creating an account on GitHub. - 151awesome-R/misc/posts.md at master ยท qinwf/awesome-R
https://github.com/qinwf/awesome-R/blob/master/misc/posts.mdA curated list of awesome R packages, frameworks and software. - qinwf/awesome-R - 152Glue strings to data in R. Small, fast, dependency free interpreted string literals.
https://github.com/tidyverse/glueGlue strings to data in R. Small, fast, dependency free interpreted string literals. - tidyverse/glue - 153The Composer of ggplots
https://github.com/thomasp85/patchworkThe Composer of ggplots. Contribute to thomasp85/patchwork development by creating an account on GitHub. - 154Pry open the covers of R
https://github.com/hadley/pryrPry open the covers of R. Contribute to hadley/pryr development by creating an account on GitHub. - 155Drat R Archive Template
https://github.com/eddelbuettel/dratDrat R Archive Template. Contribute to eddelbuettel/drat development by creating an account on GitHub. - 156create a map by R
https://github.com/Lchiffon/REmapcreate a map by R. Contribute to Lchiffon/REmap development by creating an account on GitHub. - 157A repository of learning & R resources related to topic models
https://github.com/trinker/topicmodels_learningA repository of learning & R resources related to topic models - GitHub - trinker/topicmodels_learning: A repository of learning & R resources related to topic models - 158English and European soccer results 1871-2022
https://github.com/jalapic/engsoccerdataEnglish and European soccer results 1871-2022. Contribute to jalapic/engsoccerdata development by creating an account on GitHub. - 159R package that provides complex systems datasets from the Colorado Index of Complex Networks (ICON) at https://icon.colorado.edu/.
https://github.com/rrrlw/ICONR package that provides complex systems datasets from the Colorado Index of Complex Networks (ICON) at https://icon.colorado.edu/. - rrrlw/ICON - 160Presentation Ninja ๅนป็ฏๅฟ่ ยท ๅ่ฝฎ็ผ
https://github.com/yihui/xaringanPresentation Ninja ๅนป็ฏๅฟ่ ยท ๅ่ฝฎ็ผ. Contribute to yihui/xaringan development by creating an account on GitHub. - 161A package for plotting maps in R with ggplot2
https://github.com/dkahle/ggmapA package for plotting maps in R with ggplot2. Contribute to dkahle/ggmap development by creating an account on GitHub. - 162renv: Project environments for R.
https://github.com/rstudio/renvrenv: Project environments for R. Contribute to rstudio/renv development by creating an account on GitHub. - 163Write reusable, composable and modular R code
https://github.com/klmr/boxWrite reusable, composable and modular R code. Contribute to klmr/box development by creating an account on GitHub. - 164rho-devel/rho
https://github.com/rho-devel/rhoContribute to rho-devel/rho development by creating an account on GitHub. - 165Scorecard Development in R, ่ฏๅๅก
https://github.com/ShichenXie/scorecardScorecard Development in R, ่ฏๅๅก. Contribute to ShichenXie/scorecard development by creating an account on GitHub. - 166R Interface to Python
https://github.com/rstudio/reticulateR Interface to Python. Contribute to rstudio/reticulate development by creating an account on GitHub. - 167List of courses teaching R
https://github.com/rstudio-education/rstats-edList of courses teaching R. Contribute to rstudio-education/rstats-ed development by creating an account on GitHub. - 168Coveralls.io - Test Coverage History and Statistics
https://coveralls.io/The leading provider of test coverage analytics. Ensure that all your new code is fully covered, and see coverage trends emerge. Works with most CI services. Always free for open source. - 169UTF-8 Text Processing (R Package)
https://github.com/patperry/r-utf8UTF-8 Text Processing (R Package). Contribute to patperry/r-utf8 development by creating an account on GitHub. - 170netdiffuseR: Analysis of Diffusion and Contagion Processes on Networks
https://github.com/USCCANA/netdiffuseRnetdiffuseR: Analysis of Diffusion and Contagion Processes on Networks - USCCANA/netdiffuseR - 171A guide to some of the most useful R Packages that we know about
https://github.com/rstudio/RStartHereA guide to some of the most useful R Packages that we know about - rstudio/RStartHere - 172Efficient R programming
https://csgillespie.github.io/efficientR/Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. Itโs about both computational and programmer efficiency. - 173Welcome | R for Data Science
http://r4ds.had.co.nz/This book will teach you how to do data science with R: Youโll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, youโll learn how to clean data and draw plotsโand many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. Youโll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. Youโll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data. - 174Renjin | The JVM-based interpreter for the R language for statistical computing
http://www.renjin.org/Integrate R to Java and enhance your data analysis and statistical computing with R code and packages using Renjin, the JVM-based interpreter for the R language. - 175:lock_with_ink_pen: Opinionated, typographic-centric ggplot2 themes and theme components
https://github.com/hrbrmstr/hrbrthemes:lock_with_ink_pen: Opinionated, typographic-centric ggplot2 themes and theme components - hrbrmstr/hrbrthemes - 176Tidy time series forecasting
https://github.com/tidyverts/fableTidy time series forecasting. Contribute to tidyverts/fable development by creating an account on GitHub. - 177Classes and methods for spatio-temporal data
https://github.com/edzer/spacetimeClasses and methods for spatio-temporal data. Contribute to edzer/spacetime development by creating an account on GitHub. - 178TensorFlow for R
https://github.com/rstudio/tensorflowTensorFlow for R. Contribute to rstudio/tensorflow development by creating an account on GitHub. - 179R package, using vis.js library for network visualization
https://github.com/datastorm-open/visNetworkR package, using vis.js library for network visualization - datastorm-open/visNetwork - 180Download and use Census TIGER/Line shapefiles in R
https://github.com/walkerke/tigrisDownload and use Census TIGER/Line shapefiles in R - walkerke/tigris - 181A drat repository for R Package releases including the R COBOL Data Integration (rcoboldi) and R Bitcoincharts.com API packages (rbitcoinchartsapi).
https://github.com/thospfuller/dratA drat repository for R Package releases including the R COBOL Data Integration (rcoboldi) and R Bitcoincharts.com API packages (rbitcoinchartsapi). - thospfuller/drat - 182Codecov - The Leading Code Coverage Solution
https://codecov.io/.Code coverage reporting solution for any test suite โ Codecov gives developers actionable insights to deploy reliable code with confidence. - 183Umbrella package of the 'spatstat' family................
https://github.com/spatstat/spatstatUmbrella package of the 'spatstat' family................ - GitHub - spatstat/spatstat: Umbrella package of the 'spatstat' family................ - 184A functional programming toolkit for R
https://github.com/tidyverse/purrrA functional programming toolkit for R. Contribute to tidyverse/purrr development by creating an account on GitHub. - 185A log4j derivative for R.
https://github.com/johnmyleswhite/log4rA log4j derivative for R. Contribute to johnmyleswhite/log4r development by creating an account on GitHub. - 186R-bloggers
http://www.r-bloggers.com/R news and tutorials contributed by hundreds of R bloggers - 187Easily install and load packages from the tidyverse
https://github.com/tidyverse/tidyverseEasily install and load packages from the tidyverse - tidyverse/tidyverse - 188A tidy API for graph manipulation
https://github.com/thomasp85/tidygraphA tidy API for graph manipulation. Contribute to thomasp85/tidygraph development by creating an account on GitHub. - 189Accelerated Container Application Development
https://www.docker.com/.Docker is a platform designed to help developers build, share, and run container applications. We handle the tedious setup, so you can focus on the code. - 190Exploratory Data Analysis with R
https://leanpub.com/exdataThis book teaches you to use R to visualize and explore data, a key element of the data science process. - 191Report Writing for Data Science in R
https://leanpub.com/reportwritingThis book teaches the concepts and tools behind reporting modern data analyses in a reproducible manner. - 192R package for thematic maps
https://github.com/mtennekes/tmapR package for thematic maps. Contribute to mtennekes/tmap development by creating an account on GitHub. - 193A curated list of awesome network analysis resources.
https://github.com/briatte/awesome-network-analysisA curated list of awesome network analysis resources. - briatte/awesome-network-analysis - 194R bindings to the libgit2 library
https://github.com/ropensci/git2rR bindings to the libgit2 library. Contribute to ropensci/git2r development by creating an account on GitHub. - 195Readings in applied data science
https://github.com/hadley/stats337Readings in applied data science. Contribute to hadley/stats337 development by creating an account on GitHub. - 196R COBOL DI (Data Integration) Package : Import COBOL CopyBook data files directly into R as properly structured data frames.
https://github.com/thospfuller/rcoboldiR COBOL DI (Data Integration) Package : Import COBOL CopyBook data files directly into R as properly structured data frames. - thospfuller/rcoboldi - 197a curated list of R tutorials for Data Science, NLP and Machine Learning
https://github.com/ujjwalkarn/DataScienceRa curated list of R tutorials for Data Science, NLP and Machine Learning - GitHub - ujjwalkarn/DataScienceR: a curated list of R tutorials for Data Science, NLP and Machine Learning - 198๐ Discover and install useful RStudio addins
https://github.com/daattali/addinslist๐ Discover and install useful RStudio addins . Contribute to daattali/addinslist development by creating an account on GitHub. - 199R in Action, Second Edition
http://www.manning.com/kabacoff2/R in Action, Second Edition</i> presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.</p> - 200R Cookbook, 2nd Edition
http://shop.oreilly.com/product/0636920174851.doPerform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, โฆ - Selection from R Cookbook, 2nd Edition [Book] - 201The Art of R Programming
http://shop.oreilly.com/product/9781593273842.doR is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are โฆ - Selection from The Art of R Programming [Book] - 202R Programming for Data Science
https://leanpub.com/rprogrammingLearn the fundamentals for R programming and gain the tools needed for doing data science. - 203A curated list of #rstats books
https://github.com/RomanTsegelskyi/rbooksA curated list of #rstats books. Contribute to RomanTsegelskyi/rbooks development by creating an account on GitHub. - 204Code Courses | Pluralsight
http://tryr.codeschool.com/We've integrated the interactivity from Code School into the Pluralsight platform. Grow your skills with code courses, assessments, paths and expert-led content on todayโs most in-demand technologies. - 205Static Code Analysis for R
https://github.com/jimhester/lintrStatic Code Analysis for R. Contribute to r-lib/lintr development by creating an account on GitHub. - 206Generate R package documentation from inline R comments
https://github.com/klutometis/roxygenGenerate R package documentation from inline R comments - r-lib/roxygen2 - 207An R ๐ฆ to make testing ๐
https://github.com/hadley/testthatAn R ๐ฆ to make testing ๐. Contribute to r-lib/testthat development by creating an account on GitHub. - 208Test coverage reports for R
https://github.com/jimhester/covrTest coverage reports for R. Contribute to r-lib/covr development by creating an account on GitHub. - 209An Import Mechanism For R
https://github.com/smbache/import/An Import Mechanism For R. Contribute to rticulate/import development by creating an account on GitHub. - 210Solving complex, industry-specific problems at the speed of thought
http://spotfire.tibco.com/discover-spotfire/what-does-spotfire-do/predictive-analytics/tibco-enterprise-runtime-for-r-terrSpotfire is a visual data science platform that makes smart people smarter by combining interactive visualizations and advanced analytics to solve complex industry specific business problems. - 211:no_entry: ARCHIVED
https://github.com/ropensci/opendata:no_entry: ARCHIVED :no_entry: . Contribute to ropensci-archive/opendata development by creating an account on GitHub. - 212Build software better, together
https://github.com/BZRLC/R-notes/blob/master/NLP/readme.mdGitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. - 213Generate roxygen2 skeletons populated with information scraped from the function script.
https://github.com/metrumresearchgroup/sinewGenerate roxygen2 skeletons populated with information scraped from the function script. - yonicd/sinew - 214Home
https://rweekly.orgLearn R, R tutorials, R resources, blog posts and the latest updates about the statistical programming R language. - 215CRAN Task View: WebTechnologies
https://github.com/ropensci/webservicesCRAN Task View: WebTechnologies. Contribute to cran-task-views/WebTechnologies development by creating an account on GitHub. - 216Spatial and spatio-temporal geostatistical modelling, prediction and simulation
https://github.com/edzer/gstatSpatial and spatio-temporal geostatistical modelling, prediction and simulation - r-spatial/gstat - 217Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
https://github.com/facebookincubator/prophetTool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. - facebook/prophet - 218:no_entry: ARCHIVED
https://github.com/ropensci/PackageDevelopment:no_entry: ARCHIVED :no_entry: . Contribute to ropensci-archive/PackageDevelopment development by creating an account on GitHub. - 219Encapsulated object-oriented programming for R
https://github.com/wch/R6Encapsulated object-oriented programming for R. Contribute to r-lib/R6 development by creating an account on GitHub. - 220Excerpt from the Gapminder data, as an R data package and in plain text delimited form
http://github.com/jennybc/gapminderExcerpt from the Gapminder data, as an R data package and in plain text delimited form - jennybc/gapminder - 221Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
https://github.com/jennybc/reprexRender bits of R code for sharing, e.g., on GitHub or StackOverflow. - tidyverse/reprex - 222Tools to make an R developer's life easier
https://github.com/hadley/devtoolsTools to make an R developer's life easier. Contribute to r-lib/devtools development by creating an account on GitHub. - 223Generate static html documentation for an R package
https://github.com/hadley/staticdocsGenerate static html documentation for an R package - r-lib/pkgdown - 224๐ Discover and install useful RStudio addins
https://github.com/daattali/rstudio-addins๐ Discover and install useful RStudio addins . Contribute to daattali/addinslist development by creating an account on GitHub. - 225Data Science
https://www.coursera.org/specialization/jhudatascience/1Offered by Johns Hopkins University. Launch Your Career in Data Science. A ten-course introduction to data science, developed and taught by ... Enroll for free. - 226Use R! | Book titles in this series
http://www.springer.com/series/6991?detailsPage=titlesThis series of inexpensive and focused books on R is aimed at practitioners. Books can discuss the use of R in a particular subject area (e.g., epidemiology, ...
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