For this semester, you have two options:

Only complete the part of the assignment based on your choice for computer or virtual machine!!

Your Own Computer

Install Software

##r chunk - do not change these
R.version
##                _                           
## platform       x86_64-w64-mingw32          
## arch           x86_64                      
## os             mingw32                     
## system         x86_64, mingw32             
## status                                     
## major          3                           
## minor          6.1                         
## year           2019                        
## month          07                          
## day            05                          
## svn rev        76782                       
## language       R                           
## version.string R version 3.6.1 (2019-07-05)
## nickname       Action of the Toes
#RStudio.Version() run this line but it won't knit with it "on"

ANSWER: What version of Rstudio are you using? Please note it should be the latest version! ### Install all the R Packages

  • Install the following packages, that you will need all semester:
  • markdown, knitr, reticulate, rvest, stringr, tokenizers, stringi, textclean, hunspell, tm, textstem, devtools, qdap, wordnet
  • Run this: Sys.setenv(TZ = “America/New_York”) if you see the TZ errors.
  • You may need to pay attention to the rlang package, I had to uninstall rlang and reinstall it.
  • Do not include code for knitting purposes.

Install the special R Packages

  • Use the following code to install the special packages for R.
  • Change eval = TRUE to eval = FALSE once you have them installed.

Set up your python

  • Load the reticulate library.
##r chunk
library(reticulate)
## Warning: package 'reticulate' was built under R version 3.6.3

Install Miniconda

Try typing py_config() below. You should get a prompt to install Miniconda. If not, use install_miniconda().

##r chunk

Show you’ve installed Python

Run py_config() in the R chunk below.

##r chunk
py_config()
## python:         C:/Users/punthakur/AppData/Local/Programs/Python/Python36/python.exe
## libpython:      C:/Users/punthakur/AppData/Local/Programs/Python/Python36/python36.dll
## pythonhome:     C:/Users/punthakur/AppData/Local/Programs/Python/Python36
## version:        3.6.0 (v3.6.0:41df79263a11, Dec 23 2016, 08:06:12) [MSC v.1900 64 bit (AMD64)]
## Architecture:   64bit
## numpy:          C:/Users/punthakur/AppData/Local/Programs/Python/Python36/Lib/site-packages/numpy
## numpy_version:  1.19.1

Windows Machines

Windows machines need special programs to make all this work:

Install Python Packages

  • Install the python packages by typing in R (the reticulate library must be loaded!): py_install("package_name", pip = T)
  • Change eval = TRUE to eval = FALSE once you have them installed.

Packages: nltk, matplotlib, PyQt5, scikit-learn, numpy, pandas, regex, requests, bs4, spacy, contractions, textblob, sip, gensim, afinn, pyLDAvis

Special Python Extras

For nltk, you will need to add a few other pieces. Type the following into R console: - library(reticulate) - repl_python() - Here you should notice you have switched from > to >>> which indicates you are in Python:

  • import nltk
  • nltk.download(“popular”)
  • nltk.download(“nps_chat”)
  • nltk.download(“webtext”)
  • nltk.download(“brown”)
  • nltk.download(“sentiwordnet”)
  • nltk.download(“vader_lexicon”)

To get out of >>> python, type exit or hit the Esc key.

Click on terminal > type in: - python -m spacy download en_core_web_sm - This will download the English language spacy module.

Virtual Machine

Go to: https://class.aggieerin.com/auth-sign-in

Your log in is:

Python Set Up

  • Click on terminal and run the following lines:

    • pip3 install -U spacy
    • python3 -m spacy download en_core_web_sm
    • pip3 install nltk
    • pip3 install gensim
    • python3 -m nltk.downloader popular
    • pip3 install contractions
    • pip3 install textblob
    • python3 -m nltk.downloader nps_chat
    • python3 -m nltk.downloader webtext
    • python3 -m nltk.downloader brown

Special R Package

Run the following in the R console:

  • devtools::install_github(“bnosac/RDRPOSTagger”, force = TRUE)

Turn off Miniconda

When you run py_config() the first time, it will ask you to install miniconda. Say no! We already have python3 installed on the server.

Everyone

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.
##r chunk
data(rock)
head(rock)
##   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

Call a dataset in Python

  • First, load the sklearn library, it has several sample datasets. You load python packages by using import PACKAGE. Note that you install and call this package different names (scikit-learn = sklearn).
  • Next, import the datasets part of sklearn by doing from PACKAGE import FUNCTION. Therefore, you should use from sklearn import datasets.
  • Then call the boston dataset by doing: dataset_boston = datasets.load_boston().
  • To print out the first six rows, use the .head() function: df_boston.head(), after converting the file with pandas (code included below).
##python chunk
##TYPE HERE##

import sklearn
from sklearn import datasets

dataset_boston = datasets.load_boston()

##convert to pandas
import pandas as pd
df_boston = pd.DataFrame(data=dataset_boston.data, columns=dataset_boston.feature_names)
df_boston.head()
##       CRIM    ZN  INDUS  CHAS    NOX  ...  RAD    TAX  PTRATIO       B  LSTAT
## 0  0.00632  18.0   2.31   0.0  0.538  ...  1.0  296.0     15.3  396.90   4.98
## 1  0.02731   0.0   7.07   0.0  0.469  ...  2.0  242.0     17.8  396.90   9.14
## 2  0.02729   0.0   7.07   0.0  0.469  ...  2.0  242.0     17.8  392.83   4.03
## 3  0.03237   0.0   2.18   0.0  0.458  ...  3.0  222.0     18.7  394.63   2.94
## 4  0.06905   0.0   2.18   0.0  0.458  ...  3.0  222.0     18.7  396.90   5.33
## 
## [5 rows x 13 columns]

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

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