From 941a568609c56514ff620df4ebbf7ad3a5f0fabe Mon Sep 17 00:00:00 2001 From: Abel Vertesy Date: Mon, 25 Nov 2019 13:00:36 +0100 Subject: [PATCH] readme update v4 --- README.md | 22 +++++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 18f0be8..3edecda 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ - **Formatted session info Sessioninfo** - Updated dependencies -- Many func +- Many functions are more stable and versatile @@ -42,13 +42,25 @@ I do exploratory data analysis as a daily routine, and I have constant interacti I often have to... -1. ...write emails summarising the results (text & figures) of the last few days. -2. ...find results from a couple of month back, with all tiny details (parameters used, etc). -3. ...assemble each step I did that day into a logical story line, that others can understand at first glimpse, e.g.: *I observed X; I controlled for Y; Hypothesised explanation A; Falsified it; Came up with explanation B; Tested & proven it...* +1. Make figures quickly. +2. ...write emails summarising the results (text & figures) of the last few days. +3. ...find results from a couple of month back, with all tiny details (parameters used, etc). +4. ...assemble each step I did that day into a logical story line, that others can understand at first glimpse, e.g.: *I observed X; I controlled for Y; Hypothesised explanation A; Falsified it; Came up with explanation B; Tested & proven it...* For all of the above, my solution is MarkdownReports. I think its better than other solutions I found. Many of those like to combine source code with results, and many are too complex to use. Most of people I interact with are not interested in the source code, but are very keen on seeing my results from all possible angles and are asking detailed questions about the analysis. +## Make figures quickly +- The philosophy of the package is to ***type little*** (but draw and save correctly annotated figures). +- Instead of specifying everything in lengthy commands (*ala ggplot*), plotting functions make use of sensible defaults (such as meaningful variable name, row names, column names, etc.) +- Both display and save each plot as `.pdf` dynamically named (from variable names) +- Examples: `wboxplot()` takes a list, used the `variable name` to set the *filename* and the *title*, `list element names` to set the *x-axis labels*, saves the file as `variable name.pdf` (or `.png`). +- All plot functions start with **w**, followed by the **base plot name**, such as `wplot()`, `wbarplot()`, `wpie()`, `wboxplot()`,but also `wvenn()`, `wvioplot_list()`,`wviostripchart_list()`. +- See more under: ***Discover 4 Yourself!*** (Below) + + + +## Write a report on the fly ### Differences to Rmarkdown: @@ -189,4 +201,4 @@ Abel Vertesy. (2017, October 17). MarkdownReports: An R function library to crea **MarkdownReports** is a project of @vertesy.




-[*edit the website*](https://github.com/vertesy/MarkdownReports/generated_pages/new) +[*edit the website*](https://github.com/vertesy/MarkdownReports/generated_pages/new) \ No newline at end of file