Workshop.ipynb

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   "source": [
    "<font color=#505050 size=3 face='arial black'>\n",
    "\n",
    "<font color=#505050 size=4 face='arial black'>Workshop Materials: http://bit.ly/1Kkhu3A </font><br><br>\n",
    "\n",
    "<br><br><center><font color=#505050 size=14 face='arial black'>Introduction to Python Workshop</font></center>  <br><br><center><font color=#13577F size=5 face='arial black'>Kareem Carr</font></center><br><br><br><br>\n",
    "\n",
    "<font color=#505050 size=5 face='arial black'>Data Science Services @ Harvard </font>\n",
    "<br><br>FREE advice for anybody working on publishable research at Harvard or MIT including undergraduates and graduate students (under guidance of a faculty advisor), postdocs, professors and other affiliates.  Our goal is to increase the level of computational and statistical knowledge across the Harvard and MIT research community.\n",
    "\n",
    "We provide short consultations with a data scientist on technical issues presenting a barrier to research including problems in <font color=#0E77B8>statistical analysis</font>, <font color=#0E77B8>programming</font>, <font color=#0E77B8>experiment design</font> and <font color=#0E77B8>high performance computing</font>.\n",
    "<br><br><font color=#0E77B8 size=3 face='arial black'>email: </font><a href=\"mailto:help@iq.harvard.edu\">help@iq.harvard.edu</a><br>\n",
    "<font color=#0E77B8 size=3 face='arial black'>website:</font> http://projects.iq.harvard.edu/rtc \n",
    "<br><br><br><br>\n",
    "\n",
    "<font size=5>Why Is Python Good for Data Science?</font>\n",
    "\n",
    "Python is a good language to learn if you want to:\n",
    "\n",
    "<ol>\n",
    "<li> wrangle messy or large datasets</li>\n",
    "<br>\n",
    "<li> apply machine learning to your data (http://scikit-learn.org/stable/auto_examples/plot_classifier_comparison.html)</li>\n",
    "<br>\n",
    "<li> document your analyses (http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261).</li>\n",
    "<br>\n",
    "<li> create scalable code which performs well in production </li>\n",
    "</ol>\n",
    "\n",
    "<br>\n",
    "\n",
    "<br><font color=#505050 size=5 face='arial black'>Objectives of the Workshop</font><br>\n",
    "<br>\n",
    "<font color=#505050 size=3 face='arial black'>\n",
    "\n",
    "<p>Before leaving the workshop, you should know how to:</p>\n",
    "<ol>\n",
    "\n",
    "<font color=#505050><li>Run Python code</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Perform basic operations with numbers and text</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Collect various types of data in Python</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Read data into Python from files and the internet</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Import additional commands into Python</li><br></font>\n",
    "</ol>\n",
    "\n",
    "</font>\n",
    "\n",
    "</font>\n",
    "<br>\n",
    "<br>\n",
    "<br><br><center><font color=#13577F size=6 face='arial black'>The Basics of Python</font></center><br><br>\n",
    "<br>\n",
    "<font color=#505050 size=3 face='arial black'> This workshop uses <font color=\"#13577F\">ipython notebook</font>. Howevever, there are many other ways of using Python such as spyder (similar interface to R).\n",
    "<br><br>\n",
    "The ipython notebook command starts up a local webserver that understands python commands. By default, <font color=\"#13577F\">only you</font> can see it and use it.\n",
    "<br>\n",
    "<font color=#505050 size=3 face='arial black'> During the exercise if you would like to insert a cell so you can add your own commands press <font color=\"#13577F\">ctrl-m</font> and then press <font color=\"#13577F\">b</font>. You can also click the plus symbol in the menu above.\n",
    "<br>\n",
    "<br>\n",
    "<br>\n",
    "<font color=#505050 size=4 face='arial black'>Getting started with Python.</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"Hello World!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#this is how you write a comment in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%run simple.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>A few simple Python statements</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "28428892928829829829298*2 #times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "28428892928829829829298**2 #squared"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "2.51+3.102"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "min(42,53) #minimum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "max(42,53) #maximum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "len(\"Harry Potter\") #length of the string \"It was the White Rabbit\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "round(4.5) #round values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "4 == 5 #boolean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "(4==4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'>From the point of view of the data scientist, Python is a tool for collecting and manipulating data. Most data is in the form of text and numbers. So Python has a simple system for representing numbers and text.\n",
    "<br><br>\n",
    "There are four basic types of data in Python: <font color=#13577F>boolean</font>, <font color=#13577F>strings</font>, <font color=#13577F>floats</font> and <font color=#13577F>integers</font>. Strings are text. Integers are integers, one of the two types of numbers. Floats are the equivalent of decimals. Booleans represent the truth value of various statements that we might want to ask Python.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print type(24) #integer\n",
    "print type(2.4) #float\n",
    "print type(\"It was the White Rabbit\") #string\n",
    "print type(True) #boolean\n",
    "print type(min) #function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'> Use variables to provide storage for values</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = 4\n",
    "y = 5\n",
    "z = x+y\n",
    "print x, y, z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = 5\n",
    "print type(x)\n",
    "x = \"hello\"\n",
    "print type(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'> Operations with strings</font> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "'Alice' == \"Alice\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"That's a nice hat.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "'I said, \"Good Morning\"'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"I said, \\\"Good Morning\\\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"1\\t2\" #\\t is tab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"Roses are Red\\nViolets are Blue\" #end-line character"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"White\"+\" \"+\"Rabbit\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"alice\".capitalize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"alice\".upper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"ALICE\".lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"There were doors all around the hall\".count('e')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"There were doors all round the hall\".count('all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x=4\n",
    "\"My variable contains the value %d.\" % x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x=2.6\n",
    "\"My variable contains the value %f.\" % x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x=\"cat\"\n",
    "\"My variable contains the value %s.\" % x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"   White Rabbit   \".strip()\n",
    "print \"\\t White Rabbit  \\t \".strip('\\t ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"Rabbit\".startswith(\"R\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"Rabbit\".endswith(\"t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"a\" in \"Rabbit\" #returns a boolean \n",
    "print \"doors\" in \"There were doors all round the hall\" #returns a boolean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>Getting more functions using modules</font> <br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'>You can use the import statement to get more variables in Python</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>string</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#https://docs.python.org/2/library/string.html\n",
    "import string\n",
    "\n",
    "print string.punctuation\n",
    "print string.digits\n",
    "print string.ascii_letters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'>You can use the import statement to get more functions in python as well</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>math</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#https://docs.python.org/2/library/math.html\n",
    "import math\n",
    "\n",
    "print math.pi\n",
    "print math.log(0.2)\n",
    "print math.exp(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=#505050 size=4 face='arial black'>random</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#https://docs.python.org/2/library/random.html\n",
    "import random\n",
    "\n",
    "print random.random() # random real number between 0 and 1\n",
    "print random.randint(0,5) #random integer between 0 and 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=#505050 size=4 face='arial black'>user-defined functions</font> <br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'>Whitespace is important in python. One must indent after certain special keywords, and it is important to be consistent about the use of tabs vs. spaces. I recommend always indenting with spaces.</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    return x\n",
    "\n",
    "print f(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    answer=2*x\n",
    "    return answer\n",
    "\n",
    "print f(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def f(x,y):\n",
    "    return x+y\n",
    "\n",
    "print f(2,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def count_a(sentence):\n",
    "    return sentence.count(\"a\")\n",
    "\n",
    "print count_a(\"This is sentence has two a's.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><i><font color=#13577F size=4 face='consolas'>In the box below, write a function that takes the name of a person eg. John and returns a sentence in the similar to the following: \"Hello, John! Your name contains 4 characters\"</font></i><br><br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><center><font color=#13577F size=6 face='arial black'>Getting Help</font></center><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'>\n",
    "\n",
    "<font size=4>Books</font> <br> \n",
    "\n",
    "<ol>\n",
    "\n",
    "<li><a href=\"http://learnpythonthehardway.org/\">Python the Hard Way</a> by Zed A. Shaw </li>\n",
    "\n",
    "<li><a href=\"http://shop.oreilly.com/product/0636920028154.do\">Learning Python</a> by Mark Lutz</li>\n",
    "\n",
    "<li><a href=\"http://shop.oreilly.com/category/browse-subjects/programming/python.do\">Oreilly Books</a></li>\n",
    "\n",
    "<li><a href=\"https://www.packtpub.com/all\">Packt publishing</a></li>\n",
    "\n",
    "</ol>\n",
    "<br>\n",
    "<font size=4>Websites</font>\n",
    "<ol>\n",
    "<li><a href=\"https://www.python.org/\">Python.org</a></li>\n",
    "<li><a href=\"http://stackoverflow.com/\">Stack Overflow</a></li>\n",
    "</ol>\n",
    "</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "help(math.exp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "math.exp?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "help(\"math\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dir(math)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import myfile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "help(myfile.g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%quickref #ipython help"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def h(x,y):\n",
    "\t\"\"\"h is a local function that returns x times y \"\"\"\n",
    "\treturn x*y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "help(h)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><center><font color=#13577F size=6 face='arial black'>Containers</font></center><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=#505050 size=4 face='arial black'>lists</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "x = [1,'a',min] # a simple list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "range(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x,y,z = [2.5,6.3,0.4]\n",
    "print x\n",
    "print y\n",
    "print z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"Down, down, down. Would the fall NEVER come to an end!\".split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sentence = \"Down, down, down. Would the fall NEVER come to an end!\"\n",
    "words = sentence.split()\n",
    "print sentence\n",
    "print type(sentence)\n",
    "print words\n",
    "print type(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "words = \"Down, down, down. Would the fall NEVER come to an end!\".split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print \"0   \", words[0]\n",
    "print \"1   \", words[1]\n",
    "print \"9   \", words[9]\n",
    "print \"-1  \", words[-1]\n",
    "print \"1:3 \", words[1:5]\n",
    "print \"1:  \", words[1:]\n",
    "print \"0:3 \", words[0:3]\n",
    "print \":3  \", words[:3]\n",
    "print \"len:\", len(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = ['a','c','e']\n",
    "print \"x:       \", x\n",
    "\n",
    "x.append('b')\n",
    "print \"append b:\", x\n",
    "\n",
    "x.sort()\n",
    "print \"sorted x:\", x\n",
    "\n",
    "x.remove('b')\n",
    "print \"remove b:\", x\n",
    "\n",
    "x.append('a')\n",
    "print \"append a:\", x\n",
    "\n",
    "x.append('c')\n",
    "print \"append c:\", x "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "original_sentence = \"Down, down, down. Would the fall NEVER come to an end!\"\n",
    "print \"original       :\", original_sentence\n",
    "\n",
    "no_commas = original_sentence.replace(\",\",\"\")\n",
    "print \"no commas      :\", no_commas\n",
    "\n",
    "no_exclamations = no_commas.replace(\"!\",\"\")\n",
    "print \"no exclamations:\", no_exclamations\n",
    "\n",
    "no_stops = no_exclamations.replace(\".\",\"\")\n",
    "print \"no exclamations:\", no_exclamations\n",
    "\n",
    "split_sentence = no_stops.split(\" \")\n",
    "print \"list           :\", split_sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "original_sentence.replace(\",\",\"\").replace(\"!\",\"\").replace(\".\",\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"\".join([letter for letter in original_sentence if letter not in string.punctuation])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import re\n",
    "re.sub('[!,.]','',original_sentence)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'> The FOR loop is a way of specifying an action or process that you want to apply to everything in a list. First lets print everything in a list.</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for thing in split_sentence:\n",
    "    print thing "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for word in split_sentence:\n",
    "    print word"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print random.choice(split_sentence)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'> The IF STATEMENT is a way of specifying an action that is only performed if certain conditions are met.</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for word in split_sentence:\n",
    "    if word.startswith(\"d\"):\n",
    "        print word"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "[word for word in split_sentence]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "[len(word) for word in split_sentence]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "[len(word) for word in split_sentence if word.startswith('d')]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'> The filter and map commands are somewhat advanced commands that take lists of items and produce new lists. It's okay if you don't understand them for now.</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "map(len,split_sentence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def startswith_d(word):\n",
    "    return word.startswith('d')\n",
    "\n",
    "print filter(startswith_d, split_sentence)\n",
    "print map(len, filter(startswith_d, split_sentence) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><i><font color=#13577F size=4 face='consolas'>\n",
    "In the box below, create a list that contains the words: Harry, Hermione, Ron, Luna, Remus\n",
    "<ol>\n",
    "<li>print the first element </li><br>\n",
    "<li>print the second element </li><br>\n",
    "<li>print the last element </li><br>\n",
    "<li>write a for loop that prints each name one at a time </li><br>\n",
    "<li>write a for loop that checks if a name starts with an H and stores those names in a new list </li><br>\n",
    "<li>Try to do the same thing using a combination of map and filter statements</li><br>\n",
    "</ol>\n",
    "</font></i><br><br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=#505050 size=4 face='arial black'>dictionaries</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "id_number={'Bob':'54201','Alice':'87302'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print id_number['Bob']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "category={}\n",
    "category[\"apple\"]=\"fruit\"\n",
    "category[\"banana\"]=\"fruit\"\n",
    "category[\"cherry\"]=\"fruit\"\n",
    "category[\"celery\"]=\"vegetable\"\n",
    "category[\"tomato\"]=\"vegetable\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "category[\"apple\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print category.keys()\n",
    "print sorted(category.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "category.values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "category.items()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = category.items()\n",
    "print data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print data[0][0]\n",
    "print data[0][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=3 face='arial black'> You can represent many types of information as a combination of nested lists and dictionaries.</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "students = [\n",
    "    {\"name\":{\"firstName\":\"Hermione\", \"lastName\":\"Granger\"}, \"student_id\": 9015673},\n",
    "    {\"name\":{\"firstName\":\"Ron\", \"lastName\":\"Weasley\"}, \"student_id\": 9301592},\n",
    "    {\"name\":{\"firstName\":\"Harry\", \"lastName\":\"Potter\"}, \"student_id\": 9301592}\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "students[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "students[0]['name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "students[0]['name']['firstName']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#13577F size=4 face='consolas'>\n",
    "<ol>\n",
    "<li>Write a for loop to add the student id's of the students together. Print the total.</li>\n",
    "<li>Copy the declaration of the students variable above. Manually add an extra field for each student with their ages which are 11, 10 and 10 respectively.</li>\n",
    "<li>Extra credit: Write code that takes a list of ages and adds an age field to the variable student </li>\n",
    "</ol>\n",
    "<font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <font color=#505050 size=4 face='arial black'>numpy arrays</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#http://wiki.scipy.org/Tentative_NumPy_Tutorial#head-6a1bc005bd80e1b19f812e1e64e0d25d50f99fe2\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print [1,2,3,4]+[5,6,7,8]\n",
    "print [1,2,3,4]+['a','b','c','d']\n",
    "\n",
    "x = [1,2,3,4]\n",
    "y = np.array(x)\n",
    "\n",
    "print type(x)\n",
    "print type(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "np.array([1,2,3,4])+np.array([5,6,7,8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "np.random.random(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "np.mean(np.random.random(1000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><center><font color=#13577F size=6 face='arial black'>Manipulating External Data</font></center><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>reading and writing files</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file = open(\"AliceInWonderland.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print type(file)\n",
    "print file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "text = file.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "text[0:70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file = open(\"AliceInWonderland.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file.readline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lines = file.readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lines[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file = open(\"AliceInWonderland.txt\")\n",
    "text = file.readlines()\n",
    "for line in text:\n",
    "    if line.startswith('At'): print line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file = open(\"AliceInWonderland.txt\")\n",
    "text = file.read()\n",
    "text = text.split()\n",
    "print len(text)\n",
    "print np.mean( map(len,text) ) # mean word length"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "set(['a','b','a','c','c','a'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file = open(\"AliceInWonderland.txt\")\n",
    "text = file.read()\n",
    "text = text.split()\n",
    "text = set(text)\n",
    "print len(text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>accessing webpages</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#https://docs.python.org/2/library/urllib2.html\n",
    "import urllib2\n",
    "#Project Gutenberg. Copy of Alice in Wonderland\n",
    "#http://www.gutenberg.org/cache/epub/11/pg11.txt\n",
    "webpage = urllib2.urlopen(\"http://www.gutenberg.org/cache/epub/11/pg11.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "text = webpage.readlines()\n",
    "for line in text:\n",
    "    if line.startswith('At'): print line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "webpage = urllib2.urlopen(\"http://www.gutenberg.org/cache/epub/11/pg11.txt\")\n",
    "outfile = open(\"output.txt\",'w')\n",
    "text = webpage.readlines()\n",
    "for line in text:\n",
    "    if line.startswith('At'):\n",
    "        outfile.write(line)\n",
    "outfile.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color=#505050 size=4 face='arial black'>file system</font>\n",
    "<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#https://docs.python.org/2/library/os.html\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "current_dir = os.getcwd()\n",
    "print current_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "os.listdir(current_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for root, directories, filenames in os.walk(current_dir):\n",
    "    print filenames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for root, directories, filenames in os.walk(current_dir):\n",
    "    for filename in filenames:\n",
    "        if filename.endswith(\".py\"): print filename"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for root, directories, files in os.walk(\".\"):\n",
    "    for file in files:\n",
    "        if file.endswith(\".py\"):\n",
    "            file = open(file)\n",
    "            text = file.read()\n",
    "            print len(text)\n",
    "            file.close()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=#505050 size=4 face='arial black'>graphics</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#http://matplotlib.org/\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.plot([1,2,3,4],[1,4,9,16])\n",
    "plt.ylabel('y')\n",
    "plt.xlabel('x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.plot([1,2,3,4],[1,4,9,16],color=\"red\",linestyle='--')\n",
    "plt.ylabel('y')\n",
    "plt.xlabel('x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.plot([1,2,3,4],[1,4,9,16],color=\"red\",linestyle='--')\n",
    "plt.plot([1,2,3,4],[3,7,9,8],color=\"blue\",linestyle='-.')\n",
    "plt.ylabel('y')\n",
    "plt.xlabel('x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "file = open(\"AliceInWonderland.txt\")\n",
    "text = file.read()\n",
    "text = text.split()\n",
    "data = map(len, text)\n",
    "plt.hist(data,color=\"#ff6347\")\n",
    "plt.xlim(0,16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "np.linspace(0.5,16.5,17)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.hist(data,bins=np.linspace(0.5,16.5,17),color=\"#ff6347\")\n",
    "plt.xlim(0,16)\n",
    "plt.title('Distribution of word lengths in P & P')\n",
    "plt.xlabel('word length')\n",
    "plt.ylabel('frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <font color=#505050 size=4 face='arial black'>tabular data</font> <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#http://pandas.pydata.org/\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"iris.csv\")\n",
    "print data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data[\"sepal length\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print data.ix[0]\n",
    "print\n",
    "print data.ix[0,1:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.scatter(data[\"sepal length\"],data[\"sepal width\"],color=\"#ff6347\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><center><font color=#13577F size=6 face='arial black'>Objectives of the Workshop</font></center><br>\n",
    "\n",
    "<font color=#505050 size=3 face='arial black'>\n",
    "\n",
    "<p>Before leaving the workshop, you should know how to:</p>\n",
    "<ol>\n",
    "\n",
    "<font color=#505050><li>Run Python code</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Perform basic operations with numbers and text</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Collect various types of data in Python</li><br></font>\n",
    "\n",
    "<font color=#505050><li>Read data into Python from files and the internet</li><br></font>\n",
    "\n",
    "<font color=\n",
    "\n",
    "</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><center><font color=#13577F size=6 face='arial black'>Future directions</font></center><br>\n",
    "\n",
    "<font color=#505050 size=4 face='arial black'>\n",
    "<font color=#13577F size=4 face='arial black'>Style guide</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; official python style guide: <a href=\"http://legacy.python.org/dev/peps/pep-0008/\">PEP-8</a>\n",
    "<br><br>\n",
    "<font color=#13577F>Graphics</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; matplotlib, seaborn <br><br>\n",
    "\n",
    "<font color=#505050 size=4 face='arial black'>\n",
    "<font color=#13577F>Webscraping</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; lxml, BeautifulSoup, scrapy <br><br>\n",
    "\n",
    "<font color=#13577F>Quantitative Data Analysis</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; numpy, scipy, pandas, scikit-learn, statsmodels <br><br>\n",
    "\n",
    "<font color=#13577F>Text analysis</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; pattern, textblob, nltk <br><br>\n",
    "\n",
    "<font color=#13577F>Social Network Analysis</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; networkx <br><br>\n",
    "\n",
    "<font color=#13577F>Using python with R</font> <br>\n",
    "&nbsp;&nbsp;&nbsp;&nbsp; rpy2 <br><br>\n",
    "\n",
    " </font>\n",
    " <br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br><center><font color=#13577F size=8 face='arial black'>Thanks for listening!</font></center><br><br>"
   ]
  }
 ],
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