In Ehyaei/MPIThemes: Unofficial MAX PLANCK INSTITUTE RMarkdown templates and ggplot themes

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title: "Use Python To Generate PDF Report" date: "r format(Sys.time(), '%d %B, %Y')" author: Ahmad Ehyaei disable-header-and-footer: true logo-primary: src/icon/MPILogoGray.eps output: MPIThemes::latex_report ...

source("manuscript/global.R")
library(reticulate)

Reticulate

The MPIThems templates aren't just for R programmers; due to the reticulate package, Python programmers may use them as well. The reticulate package offers a Python engine for R Markdown, allowing for simple interchange between Python and R chunks. for install reticulte use cran repository as below:

install.packages("reticulate")

Choose Python version

The first step to running Python code is to choose the Python engine or environment. There are two ways to choose a Python environment:

1. By default, reticulate uses the system Python found on your OS. To find the path, run the R command Sys.which("python") on the console. Alternatively, to use your installed Python, add your Python path with the command use_python() to set the default engine.

library(reticulate)
use_python("/usr/local/bin/python")

1. If you have an Anaconda or Miniconda, you may use the use use_condaenv() or use use_virtualenv() to run Python code in any of these environments.

use_condaenv("Python3.8", required = TRUE) # Name of environment

The Conda environment r-reticulate will be created when the reticulate package is installed. To see the list of your conda environment, run in conda list env bash or R command retculate::conda_list(). Run the py_config() command to ensure that reticulate is utilizing your updated conda env.

Install Python Package

The reticulate env has mininl Python pacakges. In order to install a new package, use py_install() command. The packages will be installed by default in r-reticulate env. For more information you can see reticulate's vignette Installing Python Packages

py_install("pandas")

Check Python working

To ensure that everything is working properly, try writing a basic Python code in RMarkdown. Set the Python command in the Python chunk {python} for this.

'''{python}
import numpy as np
import pandas as pd
np.arange(1, 10)

'''

```{python,eval=TRUE, echo=FALSE}
import numpy as np
import pandas as pd
np.arange(1, 10)

For the convenience of Python coding in RMarkdown, it is recommended that you create a shortcut to generate the python chunks. To create shortcut go to Tools -> Modify Keyboard Shortcuts and search python word to find Insert Chunk Python. Then click on it and set a suitable shortcut for it. Ctrl + Alt + P sounds a good option.

In the following example, we use the pandas package to construct a data frame and matplolib to plot the data.

```{python matplotlib,echo=TRUE,fig.height=2} import matplotlib as plt df = pd.DataFrame(data = {"x":np.arange(1,10,.01)}) df = df.assign(y=np.cos(df["x"])) df.plot(x="x", y = "y", title = "Simple Matplotlib Plot in RMarkdown")

Fortunately, Package `ggplot2` has also been implemented for Python. Below is an example of drawing a ggplot in Python

```{python ggplot,echo=TRUE,fig.height=2}
from plotnine.data import economics
from plotnine import ggplot, aes, geom_line
ggplot(df) + aes(x="x", y="y") + geom_line()

Calling Python from R

All objects created within Python chunks are available to R by calling the py$object. In the below example, we plot the previously Python-produced data with ggplot in R.

ggplot(py$df, aes(x=x, y=y)) + 
  geom_line()

Ehyaei/MPIThemes documentation built on Jan. 13, 2022, 7:28 p.m.