ecaybek

# Generates 3 GB of Swap Partition

sudo /bin/dd if=/dev/zero of=/var/swapfile bs=1M count=3072
sudo /sbin/mkswap /var/swapfile
sudo chmod 600 /var/swapfile
sudo /sbin/swapon /var/swapfile

ecaybek

myList <- list()
for(i in 1:10){
  myList[[i]] <- data.frame(a = rnorm(100, 0,1), 
                            b = rnorm(100, 0,1))
  }

library(xlsx)
for (i in 1:3){
  write.xlsx(myList[i], 
             file="test.xlsx", 

ecaybek

###### MISSING VALUE IMPLEMENTATION ##########

# Install this packages to System R
remotes::install_github("cran/BaylorEdPsych")
remotes::install_github("cran/mvnmle")
install.packages("mice")

# Select System R in Rj Editor's Settings
# Set your working directory for saving implemented data
setwd("C:/Jamovi")

ecaybek

#It must be run on Rj Editor module of Jamovi
x.data <- data #data is the jamovi data. 
x.data <- na.omit(x.data) #Remove NA values
x.center <- colMeans(x.data)
x.cov <- cov(x.data)
distance <- mahalanobis(x.data, x.center, x.cov)
cutoff <- qchisq(p = 0.999 , df = ncol(x.data)) #Cutoff value. p could be changed to 0.95, 0.99 etc.
x.data[distance > cutoff, ] #Show only outliers

#Source: https://towardsdatascience.com/mahalonobis-distance-and-outlier-detection-in-r-cb9c37576d7d

ecaybek

#In Terminal:

pacmd load-module module-remap-sink sink_name=mono master=$(pacmd list-sinks | grep -m 1 -oP 'name:\s<\K.*(?=>)') channels=2 channel_map=mono,mono
#source: https://askubuntu.com/a/99960


amixer -D pulse set Master 100%,0%
#source: https://superuser.com/a/317297

ecaybek

## This code enables Cairo in Rstudio plot preview
## Source: https://github.com/rstudio/rstudio/issues/2142#issuecomment-582096257

trace(grDevices:::png, quote({
  if (missing(type) && missing(antialias)) {
    type <- "cairo-png"
    antialias <- "subpixel"
  }
}), print = FALSE)

ecaybek

sudo apt-get install libcurl4-gnutls-dev libcurl4-openssl-dev libssl-dev libxml2-dev

ecaybek

#!/bin/bash
profilename=$1
if [[ -z $profilename ]]
then
    echo "Please enter a profile name!"
    exit
fi
if [[ $profilename = "g" ]]
then  
chromium-browser --profile-directory="Profile 1" 1>/dev/null 2>/dev/null & disown

ecaybek

# One can create test information functions
# by entering only the item parameters 
# using irtplay package.

library(irtplay)

# Creating a dataframe for item parameters
x <- data.frame(item = c("i1", "i2", "i3", "i4", "i5"),
                categ = 2,
                model = "2PLM",

ecaybek

#I couldn't save my text-mining outputs other format than pickle, which is not very useful for me.
#I can save the output as tab file with the Python script below.
#To my opinion, it's far easier than converting pickle to csv
#Connect the data to a Python Script widget and enter:

import Orange
data = in_data
data.save("C:/Py/1.tab")