A simple Notebook with R kernel on IBM Watson Studio.

R_Notebook_is_awesome_watson_studio.ipynb

Test_R_kernel_watson_studio.ipynb

{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "# Test R Notebook #\n\nThis is a test Notebook using **IBM Cloud services - Watson Studio**\n\nAuthor [mxeliezer](https://github.com/mxeliezer), R Enthusiast and quantitative researcher.\n\nStudent at [DEP - UA](https://www.ua.pt/pt/dep)."
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "### Samples of R code ###\n\nLet's try a simple vector with the ```seq()``` function and then a simple plot."
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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iABIQESEFLY2/Hx5jzVM9gfIYW5ZckiQlSY7e+aTPhBSOFtXuQ9P+ftfKLMnaoH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\njcXPtqEAAAAASUVORK5CYII=",
                        "text/plain": "plot without title"
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": "x<-seq(0,2*pi,length.out=50)\nplot(x,sin(x))"
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "### Make coding a habit ###\n\nAnd how about a litte more experimentation? Below we can see a **histogram** with randomly generated data."
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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He0nJycffv2aWcaNWrUrl07vfIAcGkU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",
                        "text/plain": "Plot with title \u201cHistogram of x\u201d"
                    },
                    "metadata": {},
                    "output_type": "display_data"
                }
            ],
            "source": "x <- rnorm(1000)\nhx <- hist(x, breaks=100, plot=FALSE)\nplot(hx, col=ifelse(abs(hx$breaks) < 1.669, 4, 2))"
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": "That's all for now. See you soon."
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "R 3.6",
            "language": "R",
            "name": "r-3.6"
        },
        "language_info": {
            "codemirror_mode": "r",
            "file_extension": ".r",
            "mimetype": "text/x-r-source",
            "name": "R",
            "pygments_lexer": "r",
            "version": "3.6.1"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 1
}