MarcinKosinski

library(mailR)
sender <- "hello@mail.com"
recipient <- "m.p.kosinski@gmail.com"
  send.mail(from = sender,
            to = recipient,
            subject = "Subject",
            body = "Hello World!",
            smtp = list(host.name = "smtp.gmail.com", port = 465, 
                        user.name = "hello@gmail.com",            
                        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),

MarcinKosinski

library(coxphSGD)
library(survival)
library(reshape2)
set.seed(456)
x <- matrix(sample(0:1, size = 20000, replace = TRUE), ncol = 2)
head(x)
dCox <- dataCox(10^4, lambda = 3, rho = 2, x,
                beta = c(2,2), cens.rate = 5)
head(dCox)

MarcinKosinski

# install.packages(c('magrittr', 'FSelectorRcpp'))
library(magrittr)
library(FSelectorRcpp)
information_gain(               # Calculate the score for each attribute
    formula = Species ~ .,      # that is on the right side of the formula.
    data = iris,                # Attributes must exist in the passed data.
    type  = "infogain",         # Choose the type of a score to be calculated.
    threads = 2                 # Set number of threads in a parallel backend.
  ) %>%                          
  cut_attrs(                    # Then take attributes with the highest rank.

MarcinKosinski

devtools::install_github("kassambara/survminer", build_vignettes = TRUE)
library("survminer")
library("survival")
fit<- survfit(Surv(time, status) ~ sex, data = lung)
ggsurvplot(
   fit,                     # survfit object with calculated statistics.
   risk.table = TRUE,       # show risk table.
   pval = TRUE,             # show p-value of log-rank test.
   conf.int = TRUE,         # show confidence intervals for 
                            # point estimaes of survival curves.