You can mix R and Python code in the same R Markdown vignette.  See:


https://bookdown.org/yihui/rmarkdown/language-engines.html


```{r "RcodeChunk"}
# R code
```

```{python "PythonCodeChunk"}
# Python code
```

I did this a couple of years ago. I haven't used Python since. However, this is described in the book Xie, Allaire, and Grolemund (2020) R Markdown: The Definitive Guide (Chapman & Hall and available for free at the above link).


          Spencer Graves


On 2021-01-27 10:31, Robert Knight wrote:
An iterative process works well. Python to get the data desired and then
Rscript script.r from a command line.   My process involves building a
script in R using, using Rstudio, Pycharm, VS Code, Kate, or some other
editor.  Then using data input built with Python as input to Rscript. The R
scripts produce excel files or CSV data for other use   RStudio is amazing
for some slow pace academic work.  The "expected a numeric but got a char"
error appeared to often for my needs and so the workflows wound up with
Python building data that's already cleaned for use in R to avoid data
import troubles.  My code use a functional paradigm rather than object
oriented paradigm.  Python does more than just munge my data since it
handled many mathematic operations on it, but it's ultimate purpose is to
clean large amounts of data to avoid import errors in R.

On Wed, Jan 27, 2021, 1:49 AM C W <tmrs...@gmail.com> wrote:

Hello all,

I'm a long time R user, but recently also using Python. I noticed that
RStudio rolled out Python through reticulate. It's great so far!

My question is, how do you debug in Python?

In R, I simply step through the code script in my console with cmd+enter.
But you can't do that with Python, some of them are objects.

Here's my example.
class person:
      def __init__(self, id, created_at, name, attend_date, distance):
           """Create a new `person`.
           """
           self._id = id
           self.created_at = created_at
           self.name = name
           self.attend_date = attend_date
           self.distance = distance

      @classmethod
           def get_person(self, employee):
           """Find and return a person by.
           """
           return person(employee['created_at'],
                employee['id'],
                employee['name'],
                employee['attend_date'],
                employee['distance']
                )

The error message says self._id was 'str', but expecting an 'int'. I can't
do:
self._id = 5
I guess it's "hidden". Can't really assign and test like that.

It seems hardcore Python programmers just use a debugger, and do not
understand the greatness of interactive IDE and console. I'd still like to
stay in IDE, hopefully.

So, how are the R users coping with object classes? Do you just instantiate
every time? What if you got 10 of these class person objects to debug?

I know this may be a Python question. But, I really wanted to see from a R
user's working experience.

Thanks a lot,

Mike

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