{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false, "slideshow": { "slide_type": "slide" } }, "outputs": [], "source": [ "%load_ext rpy2.ipython" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, "outputs": [], "source": [ "%%R\n", "X = c(1,2,3,4,5)\n", "Y = c(1,2,3,6,5)\n", "s = capture.output(summary(lm(Y~X)))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false, "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "lm(formula = Y ~ X)\n", "\n", "Residuals:\n", " 1 2 3 4 5 \n", " 1.239e-17 -2.000e-01 -4.000e-01 1.400e+00 -8.000e-01 \n", "\n", "Coefficients:\n", " Estimate Std. Error t value Pr(>|t|) \n", "(Intercept) -0.2000 1.0132 -0.197 0.8561 \n", "X 1.2000 0.3055 3.928 0.0294 *\n", "---\n", "Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n", "\n", "Residual standard error: 0.9661 on 3 degrees of freedom\n", "Multiple R-squared: 0.8372,\tAdjusted R-squared: 0.7829 \n", "F-statistic: 15.43 on 1 and 3 DF, p-value: 0.02937\n" ] } ], "source": [ "a =%R s\n", "for line in a[2:-1]:\n", " print(line )" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false, "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeAAAAHgCAMAAABKCk6nAAABwlBMVEUAAAAFBQUGBgYHBwcICAgJ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\nDAxnYLjPALb3wPFaPXcPAAAAAElFTkSuQmCC\n" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%R plot(X,Y)" ] } ], "metadata": { "celltoolbar": "Slideshow", "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.0" } }, "nbformat": 4, "nbformat_minor": 0 }