Integrating Python into your R code with reticulate

The recent introduction of the R package reticulate now allows for the seemless integration of Python coding into an R workflow. Here I’ll provide a very simple, quick example using reticulate in an RMarkdown document within RStudio, for further detail see https://github.com/rstudio/reticulate#python-in-r-markdown.

Setting up

Install the reticulate package:

install.packages('reticulate')

Running Python within an R chunk

We can now directly import packages within an R chunk in RMarkdown:

require(reticulate) # load reticulate package
os <- import("os")  # import os
os$listdir(".")     # use listdir function of os to list the contents of current dir

##  [1] "2018-04-01-introduction-to-rmarkdown.Rmd"                            
##  [2] "2018-03-27-integrating-python-into-your-r-code-with-reticulate.Rmd"  
##  [3] "2018-04-04-interactive-timelines-with-timevis.Rmd"                   
##  [4] "2018-04-03-collaborative-online-writing-with-authorea.Rmd"           
##  [5] "2018-04-01-introduction-to-rmarkdown.html"                           
##  [6] "2018-04-04-interactive-timelines-with-timevis.html"                  
##  [7] "2018-04-03-collaborative-online-writing-with-authorea.html"          
##  [8] "2018-02-11-summary-of-a-fantastic-review-paper.Rmd"                  
##  [9] "2018-03-27-integrating-python-into-your-r-code-with-reticulate_files"
## [10] "2018-04-03-setting-up-some-to-do-lists.Rmd"                          
## [11] "2018-03-27-integrating-python-into-your-r-code-with-reticulate.html" 
## [12] "2018-04-03-setting-up-some-to-do-lists.html"                         
## [13] "2018-03-28-performing-simple-linear-regressions-in-r.Rmd"            
## [14] "2018-02-11-summary-of-a-fantastic-review-paper.html"                 
## [15] "2018-03-28-performing-simple-linear-regressions-in-r.html"

Running Python within a Python chunk

Can evaluate python within a chunk:

import numpy as np
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2*np.pi*t)
print(s)

## [1.00000000e+00 1.06279052e+00 1.12533323e+00 1.18738131e+00
##  1.24868989e+00 1.30901699e+00 1.36812455e+00 1.42577929e+00
##  1.48175367e+00 1.53582679e+00 1.58778525e+00 1.63742399e+00
##  1.68454711e+00 1.72896863e+00 1.77051324e+00 1.80901699e+00
##  1.84432793e+00 1.87630668e+00 1.90482705e+00 1.92977649e+00
##  1.95105652e+00 1.96858316e+00 1.98228725e+00 1.99211470e+00
##  1.99802673e+00 2.00000000e+00 1.99802673e+00 1.99211470e+00
##  1.98228725e+00 1.96858316e+00 1.95105652e+00 1.92977649e+00
##  1.90482705e+00 1.87630668e+00 1.84432793e+00 1.80901699e+00
##  1.77051324e+00 1.72896863e+00 1.68454711e+00 1.63742399e+00
##  1.58778525e+00 1.53582679e+00 1.48175367e+00 1.42577929e+00
##  1.36812455e+00 1.30901699e+00 1.24868989e+00 1.18738131e+00
##  1.12533323e+00 1.06279052e+00 1.00000000e+00 9.37209480e-01
##  8.74666766e-01 8.12618685e-01 7.51310113e-01 6.90983006e-01
##  6.31875447e-01 5.74220708e-01 5.18246326e-01 4.64173205e-01
##  4.12214748e-01 3.62576010e-01 3.15452894e-01 2.71031373e-01
##  2.29486757e-01 1.90983006e-01 1.55672074e-01 1.23693320e-01
##  9.51729475e-02 7.02235141e-02 4.89434837e-02 3.14168389e-02
##  1.77127493e-02 7.88529869e-03 1.97327157e-03 0.00000000e+00
##  1.97327157e-03 7.88529869e-03 1.77127493e-02 3.14168389e-02
##  4.89434837e-02 7.02235141e-02 9.51729475e-02 1.23693320e-01
##  1.55672074e-01 1.90983006e-01 2.29486757e-01 2.71031373e-01
##  3.15452894e-01 3.62576010e-01 4.12214748e-01 4.64173205e-01
##  5.18246326e-01 5.74220708e-01 6.31875447e-01 6.90983006e-01
##  7.51310113e-01 8.12618685e-01 8.74666766e-01 9.37209480e-01
##  1.00000000e+00 1.06279052e+00 1.12533323e+00 1.18738131e+00
##  1.24868989e+00 1.30901699e+00 1.36812455e+00 1.42577929e+00
##  1.48175367e+00 1.53582679e+00 1.58778525e+00 1.63742399e+00
##  1.68454711e+00 1.72896863e+00 1.77051324e+00 1.80901699e+00
##  1.84432793e+00 1.87630668e+00 1.90482705e+00 1.92977649e+00
##  1.95105652e+00 1.96858316e+00 1.98228725e+00 1.99211470e+00
##  1.99802673e+00 2.00000000e+00 1.99802673e+00 1.99211470e+00
##  1.98228725e+00 1.96858316e+00 1.95105652e+00 1.92977649e+00
##  1.90482705e+00 1.87630668e+00 1.84432793e+00 1.80901699e+00
##  1.77051324e+00 1.72896863e+00 1.68454711e+00 1.63742399e+00
##  1.58778525e+00 1.53582679e+00 1.48175367e+00 1.42577929e+00
##  1.36812455e+00 1.30901699e+00 1.24868989e+00 1.18738131e+00
##  1.12533323e+00 1.06279052e+00 1.00000000e+00 9.37209480e-01
##  8.74666766e-01 8.12618685e-01 7.51310113e-01 6.90983006e-01
##  6.31875447e-01 5.74220708e-01 5.18246326e-01 4.64173205e-01
##  4.12214748e-01 3.62576010e-01 3.15452894e-01 2.71031373e-01
##  2.29486757e-01 1.90983006e-01 1.55672074e-01 1.23693320e-01
##  9.51729475e-02 7.02235141e-02 4.89434837e-02 3.14168389e-02
##  1.77127493e-02 7.88529869e-03 1.97327157e-03 0.00000000e+00
##  1.97327157e-03 7.88529869e-03 1.77127493e-02 3.14168389e-02
##  4.89434837e-02 7.02235141e-02 9.51729475e-02 1.23693320e-01
##  1.55672074e-01 1.90983006e-01 2.29486757e-01 2.71031373e-01
##  3.15452894e-01 3.62576010e-01 4.12214748e-01 4.64173205e-01
##  5.18246326e-01 5.74220708e-01 6.31875447e-01 6.90983006e-01
##  7.51310113e-01 8.12618685e-01 8.74666766e-01 9.37209480e-01]