reprex
deps
| reprex | deps | |
|---|---|---|
| 16 | 1 | |
| 729 | 30 | |
| 0.3% | - | |
| 7.4 | 6.4 | |
| 4 months ago | 6 months ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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reprex
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Do the work
Provide us with the code in a minimum working example (MWE) form (typically called reprex in the R community). If the process of producing this doesn't help you solve the issue, it at least allows us to (a) copy and paste to run the code, and (b) far more likely to be able to spot the error(s) than when they’re embedded in a load of code that isn’t necessary to highlight the problem. These should be placed in a code block, either every line indented 4 spaces or within backticks. (Credit to Mooks79 for this.) More info here: https://www.reddit.com/r/learnpython/wiki/faq#wiki_how_do_i_format_code.3F
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What is the best way to simplify a ggplot with 10 factors?
Let me start by saying it's generally preferred that you offer a reprex in a post like this, meaning at a minimum you should share (1) the minimal necessary code to reproduce your issue and (2) at least a toy data set that can be used to test your code (so, not a screen shot but maybe something created by dput(WSD), dpasta(WSD), or the like). I personally would prefer that you also format your code as a code block in your post to make it easier to read, but that's not a deal breaker (just me being fastidious).
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Help with RStudio and Giant Odds Ratios
Is reproducible example would be a nice start: https://reprex.tidyverse.org/
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Dplyr t test help
It's really hard to help you debug without a reprex
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Returning matching subsets of data based on multiple conditions
df_sl = data.frame( SubLvlList = c( '1-Z', '2-Z', '1-Y', '2-Y' ) ) data.frame( ReturnMatch = sapply( df_tl[,1], function(x) { df_sl[,1][sapply(df_sl[,1], function(y) {grepl(y, x)})] }, USE.NAMES = FALSE) ) #> ReturnMatch #> 1 1-Z #> 2 1-Z #> 3 2-Z #> 4 2-Z #> 5 1-Y #> 6 1-Y #> 7 2-Y #> 8 2-Y #> 9 1-Z #> 10 1-Z #> 11 2-Z #> 12 2-Z #> 13 1-Y #> 14 1-Y #> 15 2-Y #> 16 2-Y ``` Created on 2023-03-25 with [reprex v2.0.2](https://reprex.tidyverse.org)
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I keep getting error: "Error in t1(.) : could not find function "t1""
Making a reproducible example is a super good way to check that you are running what you think you are running.
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Very new to R and I am trying to merge 2 data frames by similar columns
reprex::reprex()
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HELP
What you have posted is not valid R code. See https://reprex.tidyverse.org/ for example on how to create a reproducible example.
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Why does converting a list to a vector require using the "unlist" function?
``` Created on 2022-11-11 with reprex v2.0.2
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Any idea why the scale of my ggplot is pushed to a corner on the left rather than having it spread across the whole plot?
https://reprex.tidyverse.org A sample of the code might help in understanding what happened
deps
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Manage Dependencies with the deps R Package for Docker Containers
The following example is part of the deps package examples. We will use a Shiny app that we have used before to draw a 3D surface for a bivariate Normal distribution.
What are some alternatives?
rna-seq-kallisto-sleuth - A Snakemake workflow for differential expression analysis of RNA-seq data with Kallisto and Sleuth.
rspm - RStudio Package Manager
papaja - papaja (Preparing APA Journal Articles) is an R package that provides document formats to produce complete APA manuscripts from RMarkdown-files (PDF and Word documents) and helper functions that facilitate reporting statistics, tables, and plots.
capsule - An inversion of renv for low effort reproducible R package libraries
workflowr - Organize your project into a research website
gittargets - Data version control for reproducible analysis pipelines in R with {targets}.
rmarkdown - Dynamic Documents for R
targets-minimal - A minimal example data analysis project with the targets R package
mindr - an R package which converts markdown files (.md, .Rmd) into mindmaps (brainstorms)
targets - Function-oriented Make-like declarative workflows for R
electionca - Canadian Elections Data
drake - An R-focused pipeline toolkit for reproducibility and high-performance computing