Executive 1: Software Overview

NOTE: All instructions in capital letters indicate code that you should fill in with the appropriate information.

Set up your python

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

library(reticulate)

• 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().

py_config()

## python:         D:\Development\Anaconda\envs\r-reticulate\python.exe
## libpython:      D:/Development/Anaconda/envs/r-reticulate/python36.dll
## pythonhome:     D:\Development\Anaconda\envs\r-reticulate
## version:        3.6.7 (default, Dec  6 2019, 07:03:06) [MSC v.1900 64 bit (AMD64)]
## Architecture:   64bit
## numpy:          D:\Development\Anaconda\envs\r-reticulate\lib\site-packages\numpy
## numpy_version:  1.17.3
## 
## python versions found: 
##  D:\Development\Anaconda\envs\r-reticulate\python.exe
##  D:\Development\Anaconda\python.exe

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.

data(rock)
head(rock,6)

##   area    peri     shape perm
## 1 4990 2791.90 0.0903296  6.3
## 2 7002 3892.60 0.1486220  6.3
## 3 7558 3930.66 0.1833120  6.3
## 4 7352 3869.32 0.1170630  6.3
## 5 7943 3948.54 0.1224170 17.1
## 6 7979 4010.15 0.1670450 17.1

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").

py_module_available("numpy")

## [1] TRUE

py_module_available("nltk")

## [1] TRUE

py_module_available("seaborn")

## [1] TRUE

py_module_available("spacy")

## [1] TRUE

py_module_available("numpy")

## [1] TRUE

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

##r chunk
#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().

##python chunk
import seaborn
VARNAME = seaborn.load_dataset("dots")
VARNAME.head()

##   align choice  time  coherence  firing_rate
## 0  dots     T1   -80        0.0    33.189967
## 1  dots     T1   -80        3.2    31.691726
## 2  dots     T1   -80        6.4    34.279840
## 3  dots     T1   -80       12.8    32.631874
## 4  dots     T1   -80       25.6    35.060487

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).

py$VARNAME$time

##   [1]  -80  -80  -80  -80  -80  -80  -60  -60  -60  -60  -60  -60  -40  -40  -40
##  [16]  -40  -40  -40  -20  -20  -20  -20  -20  -20    0    0    0    0    0    0
##  [31]   20   20   20   20   20   20   40   40   40   40   40   40   60   60   60
##  [46]   60   60   60   80   80   80   80   80   80  100  100  100  100  100  100
##  [61]  120  120  120  120  120  120  140  140  140  140  140  140  160  160  160
##  [76]  160  160  160  180  180  180  180  180  180  200  200  200  200  200  200
##  [91]  220  220  220  220  220  220  240  240  240  240  240  240  260  260  260
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## [121]  320  320  320  320  340  340  340  340  340  360  360  360  360  360  380
## [136]  380  380  380  380  400  400  400  400  400  420  420  420  420  420  440
## [151]  440  440  440  460  460  460  460  480  480  480  480  500  500  500  500
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## [181]  600  600  600  620  620  620  640  640  660  660  680  680  700  720  -80
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## [391]  700  700  720  720 -600 -580 -560 -560 -540 -540 -520 -520 -500 -500 -500
## [406] -480 -480 -480 -460 -460 -460 -440 -440 -440 -440 -420 -420 -420 -420 -400
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## [481] -140 -140 -140 -140 -140 -140 -120 -120 -120 -120 -120 -120 -100 -100 -100
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## [511]  -40  -40  -40  -40  -40  -40  -20  -20  -20  -20  -20  -20    0    0    0
## [526]    0    0    0   20   20   20   20   20   20   40   40   40   40   40   40
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## [721] -120 -120 -100 -100 -100 -100 -100 -100  -80  -80  -80  -80  -80  -80  -60
## [736]  -60  -60  -60  -60  -60  -40  -40  -40  -40  -40  -40  -20  -20  -20  -20
## [751]  -20  -20    0    0    0    0    0    0   20   20   20   20   20   20   40
## [766]   40   40   40   40   40   60   60   60   60   60   60   80   80   80   80
## [781]   80   80  100  100  100  100  100  100  120  120  120  120  120  120  140
## [796]  140  140  140  140  140  160  160  160  160  160  160  180  180  180  180
## [811]  180  180  200  200  200  200  200  200  220  220  220  220  220  220  240
## [826]  240  240  240  240  240  260  260  260  260  260  260  280  280  280  280
## [841]  280  280  300  300  300  300  300  300

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.

##python chunk
r.rock["shape"]

## 0     0.090330
## 1     0.148622
## 2     0.183312
## 3     0.117063
## 4     0.122417
## 5     0.167045
## 6     0.189651
## 7     0.164127
## 8     0.203654
## 9     0.162394
## 10    0.150944
## 11    0.148141
## 12    0.228595
## 13    0.231623
## 14    0.172567
## 15    0.153481
## 16    0.204314
## 17    0.262727
## 18    0.200071
## 19    0.144810
## 20    0.113852
## 21    0.291029
## 22    0.240077
## 23    0.161865
## 24    0.280887
## 25    0.179455
## 26    0.191802
## 27    0.133083
## 28    0.225214
## 29    0.341273
## 30    0.311646
## 31    0.276016
## 32    0.197653
## 33    0.326635
## 34    0.154192
## 35    0.276016
## 36    0.176969
## 37    0.438712
## 38    0.163586
## 39    0.253832
## 40    0.328641
## 41    0.230081
## 42    0.464125
## 43    0.420477
## 44    0.200744
## 45    0.262651
## 46    0.182453
## 47    0.200447
## Name: shape, dtype: float64

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!