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Merge pull request #247 from coding-for-reproducible-research/improve-your-r-code-material
fix typos and tidy printing at the start of each notebook
2 parents 2838c99 + 6982781 commit 8cdec29

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‎individual_modules/improve_your_r_code/data_table.ipynb

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"cells": [
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"outputs": [
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"text": [
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"/Users/cc1333/Library/Python/3.9/lib/python/site-packages/rpy2/ipython/rmagic.py:77: UserWarning: The Python package `pandas` is strongly recommended when using `rpy2.ipython`. Unfortunately it could not be loaded (error: No module named 'pandas'), but at least we found `numpy`.\n",
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" warnings.warn('The Python package `pandas` is strongly '\n"
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],
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"source": [
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"%load_ext rpy2.ipython"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"execution_count": null,
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"remove-input"
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]
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},
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"outputs": [],
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"source": [
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"%%R\n",
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"suppressPackageStartupMessages({\n",
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" suppressMessages({\n",
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" library(data.table)\n",
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" library(dplyr)\n",
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" })\n",
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"})"
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"%load_ext rpy2.ipython"
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"# Fast Data Manipulation Using the `data.table` Package\n",
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"## Overview\n",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"text": [
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"NULL\n"
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"outputs": [],
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"source": [
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"%%R\n",
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"# Write your code here"
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.6"
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"version": "3.9.19"
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}
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},
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"nbformat": 4,

‎individual_modules/improve_your_r_code/microbenchmark.ipynb

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"cells": [
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"/Users/cc1333/Library/Python/3.9/lib/python/site-packages/rpy2/ipython/rmagic.py:77: UserWarning: The Python package `pandas` is strongly recommended when using `rpy2.ipython`. Unfortunately it could not be loaded (error: No module named 'pandas'), but at least we found `numpy`.\n",
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" warnings.warn('The Python package `pandas` is strongly '\n"
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]
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}
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],
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"source": [
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"%load_ext rpy2.ipython"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"execution_count": null,
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": [
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"remove-input"
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]
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},
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"outputs": [],
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"source": [
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"%%R\n",
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"suppressPackageStartupMessages({\n",
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" suppressMessages({\n",
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" library(microbenchmark)\n",
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" })\n",
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"})"
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"%load_ext rpy2.ipython"
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"cell_type": "markdown",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"## Measuring Speed with Microbenchmark\n",
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"One way of measuring the time taken to run an R function is to invoke the `Sys.time()` function from the `base` R package. Consider the following toy function:"
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"metadata": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.6"
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"version": "3.9.19"
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"nbformat": 4,
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"nbformat_minor": 4
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‎individual_modules/improve_your_r_code/parallelisation.ipynb

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"text": [
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"/Users/cc1333/Library/Python/3.9/lib/python/site-packages/rpy2/ipython/rmagic.py:77: UserWarning: The Python package `pandas` is strongly recommended when using `rpy2.ipython`. Unfortunately it could not be loaded (error: No module named 'pandas'), but at least we found `numpy`.\n",
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" warnings.warn('The Python package `pandas` is strongly '\n"
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],
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"%load_ext rpy2.ipython"
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"execution_count": null,
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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"tags": [
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"remove-input"
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},
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"outputs": [],
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"source": [
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"%%R\n",
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"suppressPackageStartupMessages({\n",
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" suppressMessages({\n",
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" library(parallel)\n",
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" library(parallelly)\n",
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" })\n",
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"})"
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"%load_ext rpy2.ipython"
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"cell_type": "markdown",
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"slideshow": {
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"slide_type": ""
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"tags": []
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},
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"source": [
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"# Parallelisation Using the `parallel` Package\n",
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"The following section is based off of [these notes](https://dept.stat.lsa.umich.edu/~jerrick/courses/stat506_f24/16-parallel-processing.html) written by Josh Errickson at the University of Michigan. Additional information can be found in the [documentation](https://stat.ethz.ch/R-manual/R-devel/library/parallel/doc/parallel.pdf) for the parallel package.\n",
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"name": "python",
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"version": "3.9.19"
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"nbformat": 4,

‎individual_modules/improve_your_r_code/rcpp.ipynb

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"text": [
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"/Users/cc1333/Library/Python/3.9/lib/python/site-packages/rpy2/ipython/rmagic.py:77: UserWarning: The Python package `pandas` is strongly recommended when using `rpy2.ipython`. Unfortunately it could not be loaded (error: No module named 'pandas'), but at least we found `numpy`.\n",
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" warnings.warn('The Python package `pandas` is strongly '\n"
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"execution_count": null,
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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"tags": [
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"remove-input"
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]
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},
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"outputs": [],
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"source": [
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"%%R\n",
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"suppressPackageStartupMessages({\n",
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" suppressMessages({\n",
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" library(Rcpp)\n",
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" library(microbenchmark)\n",
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" })\n",
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"})"
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"%load_ext rpy2.ipython"
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]
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"cell_type": "markdown",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"# Acceleration via `Rcpp` (advanced)\n",
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"## Overview\n",
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"version": "3.9.19"
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}
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"nbformat": 4,

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