The document discusses using the reticulate package to call Python from R. It demonstrates importing Python modules and running Python code from within R. This allows users to integrate Python into their R workflow and take advantage of packages in either language. The reticulate package installs dependencies that allow R to communicate with Python. Examples show importing and manipulating data frames, plotting Python objects in R, and using Python code chunks in RMarkdown documents. An interactive Python session can also be launched from within R.

1. Calling Python from R
Barry DeCicco
Ann Arbor R Users’ Group Meeting
October 10, 2019

2. Contents
● Reticulate Package.
● Calling Python from R.
● References.

3. Why?
● Integration of Python into R workflow.
● Move between each package, using what’s best or
most familiar.

4. What you need to do first
● Install Reticulate package (which might be installed
already, depending on knitr version) .
● Reticulate uses the default Python; you can used the
function use_python("/usr/local/bin/python") to
choose alternates.

5. First Example: Run Python Command
library(reticulate)
os <- import("os")
os$listdir(".")

6. First Example: Results
[1] ".RData"
[2] ".Rhistory"
[3] ".Rproj.user"
[4] "Calling Python from R (AARUG Meeting, Oct 10,
2019).pptx"
[5] "Clustering File 1.Rmd"
[6] "Clustering-File-1.html"
And so on

7. Second Example: Import and
Wrangle Data
py_run_string("import pandas as pd")
py_run_string("flights_python = pd.read_csv('Data/flights.csv')")
py_run_string("flights_python_dest_ORD =
flights_python[flights_python['dest']=='ORD']")
py_run_string("flights_python_dest_ORD=flights_python_dest_ORD.dropna
()")
py_run_string("flights_python_dest_ORD_shape
=flights_python_dest_ORD.shape")

8. Access Python objects with 'py$...'
shape= py$flights_python_dest_ORD_shape
Shape
> shape
[[1]]
[1] 16566
[[2]]
[1] 19

9. Access Python objects with 'py$...'
ggplot(py$flights_python_dest_ORD, aes(carrier,
arr_delay)) +
geom_point() +
geom_jitter() +
facet_wrap( ~as.factor(month)) +
scale_y_log10()

10. In Rmarkdown/knitr
Use code chunks
```{python trial_run}
import pandas as pd
flights_python = pd.read_csv("Data/flights.csv")
flights_python_dest_ORD = flights_python[flights_python['dest']=='ORD']
flights_python_dest_ORD=flights_python_dest_ORD.dropna()
flights_python_dest_ORD_shape =flights_python_dest_ORD.shape
print(flights_python_dest_ORD_shape)
```

11. Interactive Python in R
The command repl_python() will open an interactive
python session.
The cursor will change to ‘>>>’.

13. References
● ‘R Interface to Python’ https://rstudio.github.io/reticulate/
● ‘R Markdown Python Engine’
https://rstudio.github.io/reticulate/articles/r_markdown.html#engine-
setup
● Vignette on GitHub:
https://github.com/rstudio/reticulate/blob/master/vignettes/calling_pytho
n.Rmd
● ‘R and Python: Using reticulate to get the best of both worlds’
(https://www.r-bloggers.com/r-and-python-using-reticulate-to-get-the-
best-of-both-worlds/)
● Nabih Ibrahim Bawazir (LinkedIn)
https://www.linkedin.com/in/nabihbawazir/