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R - Quality Control Individual Range Chart Made Nice.

In R we have the qcc package but charts are not very nice, specially if you want to put your chart in a HTML file.

Here I describe the process of creating the chart starting by using the qcc package and ending by using our own calculations and a nice dygraphs chart.

You might avoid all the comments if you go directly to my repository:

Note. Due to github restrictions for html files sizes, the html file needs to be downloaded before you can open it.

If you want to continue here, you can see the R code and outputs I copied from the html file( QualityControl_IndividualRangeChart.html ) result from the R markdown file( QualityControl_IndividualRangeChart.Rmd ) on my repository:

# Loading needed libraries# R quality control library suppressWarnings( suppressMessages( library( qcc ) ) ) # One of the R nice charts library suppressWarnings( suppressMessages( library( dygraphs ) ) ) measurements = c( -0.001, -0.011, .2, 0.001, -0.01…
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Time Series Analysis With Documentation And Steps I Follow For Analytics Projects.

To do this I will create a prediction of the open values for Bitcoin in the next 3 days.

The process I follow is based on CRISP-DM methodology:

1.- Planning the activities.

To plan the activities I use a spread sheet document, below I show the spread sheet sample, if you would like the document, please go to the next link:

ActivityActivity DescriptionDueDateActivity OwnerStatusCommentsFunctional Requirement SpecificationA Text Document explaining the objectives of this project.4/19/2018Carlos KassabDone
Get Data For AnalysisGet initial data to create feasibility analysis4/19/2018Carlos KassabDone
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Going from zero to R-Analytics with your team

Before to continue with the posts about how to do things with R, I have decided to describe how I lead the creation of an analytics team starting from zero.

My only intention here is for this information to be useful for companies looking to create their analytics team.

Well, first the first, the people for your team.

How many people is needed will depend on your company size or on the amount of money the company wants to invest in the analytics team creation but, at least you must have 2 developers, just ensure they are real developers.

Now, it is needed to define the software to use.

Database, for this I suggest to start small, let's say, using MariaDB, or SQLServer if you want to pay for a license, just ensure you can run analytic functions, some of them call them window functions, they are very useful when doing analytics. Please read this article to know more about window functions:

ETL software, unless …

What I did to use git with Rstudio on Ubuntu 16.04 and Elementary OS Loki.

This article was updated on July 7 2018.

Before installing anything I signed up on and created my R-ANALYTICS repository:
Now the installation and setup.
1. I installed git on Ubuntu, from a terminal window:
$ sudo apt-get update $ sudo apt-get install git
2.- I configured git:
I did this through the git config command. I provided my name and email address because git embeds this information into each commit. Open a terminal and run:
$ git config --global "Your Name" --> This is part of your link:, you see, my name is LaranIkal $ git config --global ""
To see all of the configuration items just type:
$ git config --list
As a note, it is saved to a file called ~/.gitconfig in your home folder.
Steps In Rstudio:

1.- Checking/Setting Rstudio right configuration to use Git/SVN: Menu→Tools→Global Options Select GIT/SVN tab at the …