MarcinKosinski

predict_lda <- function(...) 
  get('predict.lda', envir = asNamespace('MASS'), inherits = FALSE)(...)

MarcinKosinski

# what it was
{if({my_stat} == "avg") {dplyr::summarise(., stat = mean(var_agg, na.rm = TRUE)) %>%
        dplyr::pull(stat) %>% formattable::comma(label_digits)}
      else if({my_stat} == "max") {dplyr::summarise(., stat = max(var_agg, na.rm = TRUE)) %>%
          dplyr::pull(stat) %>% formattable::comma(label_digits)}
      else if({my_stat} == "min") {dplyr::summarise(., stat = min(var_agg, na.rm = TRUE))

# what it can be
possible values of my_stat are renamed to so that `avg` is now `mean`

MarcinKosinski

@Article{assel,
	author = {Asselain, B. and Mould, R. F.},
	title = {Methodology of the {Cox} proportional hazards model},
	journal = {Journal of Oncology},
	year = {2010},
	volume = {60},
	number = {5},
	pages = {403--409}}
  
@Book{boxst,

MarcinKosinski

library(mailR)
sender <- "[email protected]"
recipient <- "[email protected]"
  send.mail(from = sender,
            to = recipient,
            subject = "Subject",
            body = "Hello World!",
            smtp = list(host.name = "smtp.gmail.com", port = 465, 
                        user.name = "[email protected]",            
                        passwd = pwd, 

MarcinKosinski

download.file('https://github.com/MarcinKosinski/trigeR5/raw/master/dicts/polimorfologik-2.1.zip', destfile = 'poli.zip')
unzip('poli.zip', exdir = 'dicts')
library(data.table);library(dplyr)
polimorfologik <- fread('dicts/polimorfologik-2.1.txt', data.table = FALSE) %>% set_colnames(c('stem', 'words', 'random_stuff')) %>% select(1:2) 
random_polish_text <- 
  'Wbrew wcześniejszym doniesieniom mediów, w bazie pod Latok I (szczyt w masywie w grupie Panmah Muztagh, części Karakorum), gdzie organizowana jest pomoc dla Aleksandra Gukowa (rosyjski himalaista nadał sygnał SOS i musi zostać ewakuowany, bo jest pozbawiony ekwipunku), nie ma też Andrzeja Bargiela. - Andrzej zgłosił chęć pomocy i wzięcia udziału w akcji ratunkowej. Jednak obecnie znajduje się w Skardu, gdzie dotarł wczoraj z bazy pod K2 - czytamy na twitterowym koncie pierwszego człowieka w historii, który zjechał z wierzchołka K2.'

(polish_stop_words <- readLines('https://raw.githubusercontent.com/MarcinKosinski/trigeR5/master/dicts/polish_stopwords.

MarcinKosinski

\documentclass[15pt]{scrartcl}
\usepackage[a6paper,left=1cm,right=1cm,top=2cm,bottom=1cm,heightrounded]{geometry}
\usepackage[svgnames]{xcolor}
\usepackage{pdflscape}
\usepackage{setspace}
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage{graphicx}
\usepackage{wallpaper}
\usepackage[normalem]{ulem}

MarcinKosinski

library(dplyr);library(crunch)
iris_ds <- 
  newDataset(iris, name = 'iris')

# how to add the following data.frame as a CrunchCube or something similar to the Array?
iris_ds$some_statistics <- 
  iris %>%
  group_by(Species) %>%
  summarize_all(funs(mean))

MarcinKosinski

ggsurv <- ggsurvplot(
  fit,                     # survfit object with calculated statistics.
  data = BRCAOV.survInfo,  # data used to fit survival curves.
  risk.table = TRUE,       # show risk table.
  pval = TRUE,             # show p-value of log-rank test.
  conf.int = TRUE,         # show confidence intervals
  xlim = c(0,2000),        # present narrower X axis, but not affect
  # survival estimates.
  xlab = "Time in days",   # customize X axis label.
  break.time.by = 500,     # break X axis in time intervals by 500.

MarcinKosinski

library(rgdal)    # read and store spatial data
library(dplyr)    # manipulate data frames for data wrangling
library(leaflet)  # connect to LeafletJS library from R
library(magrittr) # pipe workflows
library(openxlsx) # read xlsx files
library(readxl)   # read xls  files

# prepare the data ------------------------------------------------------------
# read MSA layer 

MarcinKosinski

extractSurvival <- function(cohorts){
  
  survivalData <- list()
  for(i in cohorts){
    get(paste0(i, ".clinical"), envir = .GlobalEnv) %>%
				select(patient.bcr_patient_barcode,
							 patient.vital_status,
							 patient.days_to_last_followup,
							 patient.days_to_death ) %>%
				mutate(bcr_patient_barcode = toupper(patient.bcr_patient_barcode),