rblander edits

Author: Steve Weber

Extras/Data/AirPassengers.csv

@@ -74,7 +74,7 @@
    "id": "998fdd38-6348-4853-ab6d-86467d13d5d3",
    "metadata": {},
    "source": [
-    "## Spencer Mcconville, Spring 2022 Compuational Research Assistant <br/> University of Waterloo, Math Faculty Computing Facility"
+    "## Spencer McConville, Spring 2022 Computational Research Assistant <br/> Math Faculty Computing Facility, University of Waterloo"
    ]
   },
   {
@@ -132,9 +132,9 @@
     "# 1 - Introduction\n",
     "This document is meant to be used as a reference and/or guide for students learning data science applications in R or Python for the first time. Individuals will most likely find this information more useful if they have prior knowledge in either R or Python and are trying to learn one or the other. There is a strong emphasis throughout this document on creating similar results in both languages and how to reproduce the results of one language in the other.\n",
     "\n",
-    "R and Python are two different languages created by different people for different reasons. R was designed for statistical computing and computation, created by statisticians. On the other hand Python is a general purpose, object oriented language designed to highlight programmer productivity and flexibility. It wasn't until data science applications became more popular that people started to use the two languages for the same tasks. Modern day packages for both languages now allow one to perform such tasks in a way that there may be no clear advantage in using one over the other.\n",
+    "R and Python are two different languages created by different people for different reasons. R was designed for statistical computing, created by statisticians. On the other hand Python is a general purpose, object oriented language designed to highlight programmer productivity and flexibility. It wasn't until data science applications became more popular that people started to use the two languages for the same tasks. Modern day packages for both languages now allow one to perform such tasks in a way that there may be no clear advantage in using one over the other.\n",
     "\n",
-    "When it comes to data science applications, the two languages have code bases which are structured much differently. One can think of R as a collection of many smaller packages built on top of R's built-in functions. These smaller packages each have their own functions to perform specific tasks. Python can be thought of as a collection of larger packages. These larger packages can usually perform a wide range of tasks and can be used for multiple reasons. For example Python's PyTorch module can be used in many different areas of machine learning. Essentially, this can be broken down into a decision of either learning a large number of smaller R packages or learning a small number of larger Python modules.\n",
+    "When it comes to data science applications, the two languages have code bases which are structured much differently. One can think of R as a collection of many smaller packages built on top of R's built-in functions. These smaller packages each have their own functions to perform specific tasks. Python can be thought of as a collection of larger packages. These larger packages can usually perform a wide range of tasks and can be used for multiple purposes. For example Python's PyTorch module can be used in many different areas of machine learning. Essentially, this can be broken down into a decision of either learning a large number of smaller R packages or learning a small number of larger Python modules.\n",
     "\n",
     "If you have not learned either R or Python yet and do not know which to choose, I recommend doing some additional research on both of these languages. I would start off by watching all or a subset of these Youtube videos:  \n",
     "* [[1] R Vs Python | Which is Better for Data Analysis?](#ref1)   \n",
@@ -219,6 +219,14 @@
     "[6] R Core Team, 2020. R: A Language and Environment for Statistical Computing, [[link]](https://www.R-project.org) <a class=\"anchor\" id=\"ref6\"></a>      \n",
     "[7] Van Rossum, G. & Drake, F.L., 2009. Python 3 Reference Manual, [[link]](https://www.python.org/) <a class=\"anchor\" id=\"ref7\"></a>  "
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bd63bdd0-431b-427e-9d97-adbbd0aaea93",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -237,7 +245,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.10"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,