SchmidtPaul

Chapter 1: R Intro
https://schmidtpaul.github.io/dsfair_quarto/rbasics/firststeps.html

Chapter 2: Tidyverse
https://schmidtpaul.github.io/dsfair_quarto/rbasics/tidyverse.html

Chapter 3: Correlation & Regression
https://schmidtpaul.github.io/dsfair_quarto/rbasics/correlation_regression.html

Chapter 4: Bad Data & Outlier

SchmidtPaul

[
  {
    "cmd": "Py",
    "act": "Python Code Assistant",
    "prompt": "You are my Python Code Assistant. Whenever you help me with Python code, I want the following things: Never tell me to or show me how to install and/or load a module. Instead, skip right to the actual code. 2. Never reproduce a array/dataframe etc. that I pasted unless I explicitly ask you to. Instead, skip right to the actual code where you can refer to any of my arrays/dataframes either with their name or - if no name was provided - with dummy names like `your_array`. 3. Make use of numpy, pandas and piping. 4. I dont care whether you actually run python code or not, however the answer must always be Python code which I can easily copy-paste 5. Always immediately start with the code. Any additional explanations should be written at the very end of your response.",
    "enable": true
  },
  {
    "cmd": "R",
    "act": "R Code Assistant",

SchmidtPaul

You are my R Code Assistant. Whenever you help me with R code, I want the following things: 1. Never tell me to or show me how to install and/or load a package. Instead, skip right to the actual code. 2. Never reproduce a table/vector etc. that I pasted unless I explicitly ask you to. Instead, skip right to the actual code where you can refer to any of my tables/vectors either with their name or - if no name was provided - with dummy names like `your_table`. 3. Make use of the tidyverse and pipes (%>%). If applicable and advantageous, also make use of {lubridate}, {purrr} and/or {scales}. 4. Always immediately start with the code. Any additional explanations should be written at the very end of your response.

SchmidtPaul

---
title: "Run SAS in R"
author: Dr. Paul Schmidt, BioMath GmbH
output: word_document
---

```{r, include = FALSE}
library(SASmarkdown)
knitr::opts_chunk$set(
  engine = "sas",

SchmidtPaul

# inspiration: https://albert-rapp.de/post/2021-12-31-ggforce-examples/

library(ggforce)
library(tidyverse)

set.seed(42)

tibble(x = runif(1000), y = runif(1000)) %>%
  ggplot(aes(x, y)) +
  geom_voronoi_tile(aes(fill = y)) +

SchmidtPaul

library(tidyverse)

# data --------------------------------------------------------------------
dat <- tibble(
  x = c("A", "A", "B", "B"),
  y = c(12, 11, 13.03, 13),
  grp = c("G1", "G2", "G1", "G2"),
  lab = c("a", "abc", "ab", "abcd")
) %>%
  mutate_if(is.character, as.factor)

SchmidtPaul

# taken from youtube tutorial: https://youtu.be/hPTBZelmAh4

library(showtext)
library(ggplot2)

font_add(family = "ComicSansMS", regular = "Comic.ttf")
showtext_auto()

labeldata <- data.frame(mylabel = "geom_text font\nmust be changed\nseparately like this",
                        group = 1.5,

SchmidtPaul

library(dlookr)
library(tidyverse)

dat <- mtcars %>% 
  transmute(Cyl = as.factor(cyl),
            Am  = as.factor(am),
            hp = hp)

bind_rows(
  dat %>% describe(hp),

SchmidtPaul

/*******************************************************************************************************/
/* First time setup:                                                                                   */
/* You must take one manual step before your SAS can run R-Code: Edit the SAS-config-file (sasv9.cfg). */
/* To locate this file on your PC, you can run the following code in SAS and it will return the        */
/* path to the SAS-config-file in the log:                                                             */
/*   proc options option=config; run;                                                                  */
/* It will possibly be: C:\Program Files\SASHome\SASFoundation\9.4\nls\en\sasv9.cfg                    */
/* Find that file and edit it as shown in this video at 1:10min (i.e. add '-RLANG')                    */
/*   https://www.youtube.com/watch?v=3pbXUthE1As&t=110s                                                */ 
/* If Windows does not allow you to save/overwrite the file after edi

SchmidtPaul

# This function exports plots. It always creates a pdf and can additionally
# create png files (defaults: create_png = TRUE; ). You provide the 
# folder_path and the file_name and by default both folder_path/file_name.pdf 
# and folder_path/file_name.png will be created.
#
# You may immediately preview the created files by automatically having them
# opened on your computer after being created (defaults: open_pdf = FALSE;
# open_png = TRUE).
#
# The pdf is exported via ggplot2::ggsave(), but the png is not! Instead,