Computer Tips - Programming, Cybersecurity and Tech Tutorials

If you are using MS Excel version older than 2016 and if Data analysis option is not available in Analysis section under Data tab then follow the instructions below. Data analysis option is not available. Go to File menu > Options > Add-Ins > Select "Excel Add-ins" in Manage drop-down list that is located at the end of the window and hit go. Then select Analysis ToolPak and click OK it will add Data Analysis option under Analysis group in Data tab. This is how it looks like after enabling the add-in.

I was using the Shiny app in R , and I was trying to read a file using fileInput control, but I faced the following error:   Listening on http://127.0.0.1:3558 Error in read.table(file = file, header = header, sep = sep, quote = quote,  :   'file' must be a character string or connection Problem code: if(is.null(input$file1))       return(NULL)  file <- read.csv(file=input$file1,head=TRUE,sep=",", stringsAsFactors=FALSE) csv <- str(file) Solution: inFile <- input$file1 if (is.null(inFile))       return(NULL)     csv <- read.csv(inFile $datapath , header=TRUE, sep=",") The resolution was to use the datapath property of the input file and not the file itself.

This tiny utility shows you public and private IP as soon as you open it so you don't need to go to any website such as whatismyip.com to find your current Public IP Address. Size: IP info.zip --> 3.94 KB IP info.exe --> 9.50 KB Download links: 1. Google Drive: https://drive.google.com/file/d/0B_HnjRcH9aTpQmNGUmw3cU5RQ2s/view?usp=sharing 2. MediaFire: http://www.mediafire.com/download/c1zn8yyh7zfsn3w/IP_info.zip 3. Kickass Torrents: https://kat.cr/ip-info-zip-t11825063.html This is a small Windows utility that shows your public and private IP address the moment you open it, so you do not have to visit a site such as whatismyip to look it up. A tiny local tool like this is convenient for quick network checks. As with any downloaded executable, run it only if you trust the source.

Download Link: https://drive.google.com/file/d/0B_HnjRcH9aTpNG10ME1raW0zdTA/view?usp=sharing (Click this link to download pdf) This PDF is a part of Introduction to R workshop conducted by Chris Bruno , Dason Kurkiewicz and Adam Loy from Department of Statistics, IOWA State University on 15 July 2010. Reference: http://streaming.stat.iastate.edu/workshops/r-intro/ Breakdown of chapters is as following: 1. Introduction 2. Data Management 3. Graphics 4. Models 5. Programming 6. Advanced Manipulations Reference: http://streaming.stat.iastate.edu/workshops/r-intro/lectures/ This post shares a downloadable PDF introduction to R from a statistics workshop, aimed at newcomers to the language. R is a free environment widely used for statistics, data analysis, and graphics. A guided introduction like this is a good starting point before moving on to packages such as ggplot2 and dplyr for visualization and data wrangling.

CODE: # '#' denotes a comment # install.packages("UsingR") uncomment if package is not installed library (UsingR) # install.packages("shiny") uncomment if package is not installed library (shiny) # install.packages("Hmisc") uncomment if package is not installed library (Hmisc) # install.packages("corrplot") uncomment if package is not installed library (corrplot) # getwd() gives the current directory where R looks up for files wd <- getwd() setwd(wd)