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The Caped Crusader says it all.
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R Programming A-Z™: R For Data Science With Real Exercises!

Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2



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In this course, you would learn the fundamentals of R programming language, including the basic concepts such as lists, functions, arrays, vectors, matrices, strings, etc.

#rprogramminglanguage #rprogrammingtutorial #learnrprogramming


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For those of us who could not make it to Brussels.

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How to create functions in R

When starting out with R, it is a common mistake to make calculations too extensive, e.g. if adding an array of numbers to a variable, raising a number to a power, etc.

Here is how functions can make this process more efficient: http://www.michaeljgrogan.com/creating-functions-in-r/ #rlang #datascience #rstats

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R Studio introduce the learnr package. The learnr package makes it easy to turn any R Markdown document into an interactive tutorial.


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Hi guys! My latest data science course, "Regression Analysis and Data Structuring Methods: R and Python" is now available. The guide focuses mainly on R (but there are a few Python examples in there as well for anyone who has an interest).

In my course, you will receive access to a 36-page manual on the use of data science techniques in R and Python. This course will teach you how to:

- Run an OLS Regression in R and test for violations
- Use statsmodels to run an OLS regression in Python
- Test a time series dataset for autocorrelation and remedy this issue
- Check for cointegration between two time series models
- Structure data effectively using data frames in R
- Create an ARIMA model in Python and R

You will receive a free copy of the course upon subscription to my mailing list, along with weekly data science newsletters sent to your inbox.

If you are interested in receiving, feel free to subscribe here: http://www.michaeljgrogan.com/data-science/

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Apparently R now on position #5 from all programming languages

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Great video series by Roger Peng. Worth watching. Ploughing into and getting dirty with R.

https://www.youtube.com/watch?v=pOA2wggeQkQ

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An update to my R data wrangling "cheat sheet". How to separate data by list (see tip 10). This can be highly useful when it comes to subsetting panel data.

Read more at: http://www.michaeljgrogan.com/data-cleaning-merging-r/ #rlang #datascience
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