Executive 1: Software Overview

Set up your python

• Install the reticulate package (do not include this code).
• Load the reticulate library.

library(reticulate)
py_config()

## python:         C:\Users\User\AppData\Local\Programs\Python\Python37\python.exe
## libpython:      C:/Users/User/AppData/Local/Programs/Python/Python37/python37.dll
## pythonhome:     C:\Users\User\AppData\Local\Programs\Python\Python37
## version:        3.7.4 (tags/v3.7.4:e09359112e, Jul  8 2019, 20:34:20) [MSC v.1916 64 bit (AMD64)]
## Architecture:   64bit
## numpy:          C:\Users\User\AppData\Local\Programs\Python\Python37\lib\site-packages\numpy
## numpy_version:  1.17.1
## 
## python versions found: 
##  C:\Users\User\AppData\Local\Programs\Python\Python37\python.exe
##  C:\Users\User\AppData\Local\Programs\Python\Python37\\python.exe

• The first you set this up, you need to configure where your Python is located.
• Run py_config() to find the python versions you have installed on your machine.
• For example, here’s mine:

python:         /usr/bin/python
libpython:      /System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/config/libpython2.7.dylib
pythonhome:     /System/Library/Frameworks/Python.framework/Versions/2.7:/System/Library/Frameworks/Python.framework/Versions/2.7
version:        2.7.16 (default, Oct 17 2019, 17:14:30)  [GCC 4.2.1 Compatible Apple LLVM 11.0.0 (clang-1100.0.32.4) (-macos10.15-objc-s
numpy:          /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy
numpy_version:  1.8.0

python versions found: 
 /usr/bin/python
 /usr/bin/python3
 /usr/local/bin/python3
 /Users/buchanan/anaconda3/bin/python

• Next, we want to configure which one to use.
• If the one listed next to python on the top line is the one you want to use, you are all done.
• If not, you will copy the path (i.e. /Users/buchanan/...) and tell R to talk to that python instead.
• To do that, you would use: use_python("PATH", required = TRUE).
• However, you can’t run use_python() after running py_config(). You will get an error message:

ERROR: The requested version of Python
('/Users/buchanan/anaconda3/bin/python') cannot be used, as
another version of Python ('/usr/bin/python') has already
been initialized. Please restart the R session if you need
to attach reticulate to a different version of Python.
Error in use_python("/Users/buchanan/anaconda3/bin/python", required = TRUE) : 
  failed to initialize requested version of Python

• Click Session > Restart R.
• Then use your use_python() code.
• Do not include BOTH py_config() and use_python() in the same markdown. Once you know where your path is, just use use_python().

Let’s do some R

• In this chunk, we will load a dataset - use data(rock) to load it.
• Use the head() function to print out the first six rows of the dataset.

Let’s do some Python

• First, let’s install some packages.
• You will need numpy, nltk, spacy, seaborn and pandas for starters.

• You can check if you have them first by using py_module_available("PACKAGE").

• If any of these return FALSE, then install them using py_install("PACKAGE").

#if they are all TRUE, leave this blank

Call a dataset in Python

• First, load the seaborn library, it has several sample datasets. You load python packages by using import PACKAGE.
• Then call the dots dataset by doing: VARNAME = PACKAGENAME.load_dataset("DATASETNAME").
• To print out the first six rows, use the .head() function: VARNAME.head().

QUESTION: Look in your environment window. What do you see?

Print out Python information in R

• You can have the two environments interact. To print out information from Python in R: py$VARNAME.
• Normally, to print out R dataset columns, you do DATAFRAME$COLUMN. Try to print out the time column from your dots variable (whatever you named it above).

Print our R in Python

• When using R in Python, instead of $, we use . like this: r.VARNAME.
• To print out a single column, you use DATAFRAME["COLUMNNAME"]. Try printing out the shape column in the rock dataset.

Get started with PyCharm!

• Great job! Here’s what you learned:
  • You know how to tell Rmarkdown which Python to use.
  • You know how to install and load the libraries in both languages.
  • You know how to load built in datasets in both languages.
  • You know how to print out data from one language to another.
• Turn this document in for credit –> hit KNIT –> turn in the HTML file.
• Be sure to fill in your name at the top!