Welcome to the Tutorial wiki! I have used the following reference to learn python programming "https://github.com/kuleshov/cs228-material/blob/master/tutorials/python/cs228-python-tutorial.ipynb" Some commands are not working like s.replace() of string operations.

gistfile1.txt

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7efc296b57b8>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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q/hJMgwZ+tE/WW//33QcXXxw6hWSNir8EVdH1U1YWOkkYr74KH33kb/aKFJKK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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efc2b996a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.arange(0,3*np.pi,0.1)\n",
    "y = np.sin(x)\n",
    "#plot the points using matplotlib\n",
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7efc290e1550>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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A1665byPzgrcKhQpBWBhMn65aiXWZf3A+jco2orx3FomcXJDcuqkyaVK+CWky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\nqqXkCT3i0NjM4NmD8S3sy5guYxze9/kb56n7fV0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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7efc2963f320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_cos = np.cos(x)\n",
    "y_sin = np.sin(x)\n",
    "# plot the points using matplotlib\n",
    "plt.plot(x, y_sin)\n",
    "plt.plot(x,y_cos)\n",
    "plt.xlabel('x axis label')\n",
    "plt.ylabel('y axis label')\n",
    "plt.title('Sine and Cosine')\n",
    "plt.legend(['Sine','Cosine'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[6 7]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "# Create the following ranl 2 array with shape (3,4)\n",
    "# [[1 2 3 4]\n",
    "#  [5 6 7 8]\n",
    "#  [9 10 11 12]]\n",
    "a = np.array([[1,2,3,4],[5,6,7,8],[9,10,11,12]])\n",
    "# Use slicing to pull out the subsisdiary consisting of the first 2 rows\n",
    "# and columns 1 and 2; b is the following array of shape (2,2):\n",
    "# [[2,3]\n",
    "# [6,7]]\n",
    "b = a[1:2,1:3] # The slicing operation is a little bit weird for matlab user\n",
    "print(b)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}

Tutorial_1

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 1, 2, 3, 6, 8, 10]\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Python is a high-level,dynamically typed multiparadigm language. Python code is often said to be almost like \n",
    "pseudocode,since it allows you to express very powerful ideas in very few lines of code while being very readable\"\"\"\n",
    "# quicksort\n",
    "import numpy as np\n",
    "def quicksort(arr):\n",
    "    if len(arr) <= 1:\n",
    "        return arr\n",
    "    pivot = arr[np.uint8(len(arr)/2)]\n",
    "    left = [x for x in arr if x < pivot]\n",
    "    middle = [x for x in arr if x == pivot]\n",
    "    right = [x for x in arr if x> pivot]\n",
    "    return quicksort(left)+middle+quicksort(right)\n",
    "print(quicksort(np.uint8([3,6,8,10,1,2,1])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 <class 'int'>\n"
     ]
    }
   ],
   "source": [
    "# Basic data Types\n",
    "# numbers\n",
    "x = 3\n",
    "print (x, type(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "2\n",
      "6\n",
      "9\n"
     ]
    }
   ],
   "source": [
    "print(x+1) # addition\n",
    "print(x-1) # subtraction\n",
    "print(x*2) # Multiplication\n",
    "print(x**2)# Exponentiation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4\n",
      "8\n",
      "6\n"
     ]
    }
   ],
   "source": [
    "x += 1 \n",
    "print(x) # prints \"4\"\n",
    "x *= 2\n",
    "print(x) # prints \"8\"\n",
    "x -=2 \n",
    "print(x) # prints \"6\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'float'>\n",
      "2.5 3.5 5.0 6.25\n"
     ]
    }
   ],
   "source": [
    "y = 2.5\n",
    "print(type(y)) # prints \"<type 'float'>\"\n",
    "print(y,y+1,y*2,y**2) #prints \"2.5 3.5 5.0 6.25\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'bool'>\n",
      "False\n",
      "True\n",
      "False\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "t,f = True, False\n",
    "print(type(t))  # prints \"<type 'bool'>\"\n",
    "print (t and f) # logical AND;\n",
    "print (t or f) # logical OR;\n",
    "print (not t) # logical NOT;\n",
    "print (t!=f) #logical Xor;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "unexpected EOF while parsing (<ipython-input-16-9ffbc4f99f3d>, line 16)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-16-9ffbc4f99f3d>\"\u001b[1;36m, line \u001b[1;32m16\u001b[0m\n\u001b[1;33m    #print('    world    '.strip()) # strip leading and trailing whitespace; prints \"world\"\u001b[0m\n\u001b[1;37m                                                                                           ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m unexpected EOF while parsing\n"
     ]
    }
   ],
   "source": [
    "hello = 'hello' # string literals can use single quotes\n",
    "world = \"world\" # 04 Double quotes; it does not matter.\n",
    "print(hello,len(hello))\n",
    "# string concatenation\n",
    "hw = hello + '' + world # string concatenation\n",
    "print(hw) # prints \"hello world\"\n",
    "hw12 = '%s %s %d' %(hello,world,12) # sprintf style string formatting\n",
    "print(hw12) # prints\"hello world 12\"\n",
    "s = \"hello\"\n",
    "print( s.capitalize()) # capitalize a string; prints \"Hello\"\n",
    "print(s.upper()) # Convert a string to uppercase; prints \"HELLO\"\n",
    "print(s.rjust(7))# Right-justify a string, padding with spaces; print \"    hello\"\n",
    "print(s.center(7) # center a string, padding with spaces; prints \"   hello   \"\n",
    "#print(s.replace('l','(ell)'))# Replace all instances of one substring with another;\n",
    "                              #prints \"he(ell)(ell)o\"\n",
    "#print('    world    '.strip()) # strip leading and trailing whitespace; prints \"world\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 1, 2] 2\n",
      "[3, 1, 'foo']\n",
      "[3, 1, 'foo', 'bar']\n",
      "bar\n"
     ]
    }
   ],
   "source": [
    "# Containers - Python includes several built-in container types: lists, dictionaries, sets and tuples.\n",
    "# Lists - A List is the python equivalent of an array, but is resizeable and \n",
    "# can contain elements of different types\n",
    "xs = [3,1,2]   # Create a List\n",
    "print(xs,xs[2])\n",
    "#print xs[-1]   # Negative indices count from the end of the list; prints \"2\"\n",
    "xs[2] = 'foo'  # Lists can contain elements of different types\n",
    "print(xs)\n",
    "xs.append('bar') # Lists cana contain elements of different types\n",
    "print(xs)\n",
    "x=xs.pop() # Remove and Return the last element of the list\n",
    "print(x)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "foo\n"
     ]
    }
   ],
   "source": [
    "x=xs.pop() # Remove and Return the last element of the list\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "range(0, 5)\n",
      "range(2, 4)\n",
      "range(2, 5)\n",
      "range(0, 2)\n"
     ]
    }
   ],
   "source": [
    "# Slicing : In addition to accessing list elements one at a time, \n",
    "# Python  provides concise syntax to access sublists; This is known as slicing\n",
    "nums = range(5)     # range is a built-in function that creates a list of integers\n",
    "print(nums)           # Prints \"[0,1,2,3,4]\"\n",
    "print(nums[2:4])     # Get a slice from index 2 to 4 (exclusive); prints \"[2,3]\"\n",
    "print(nums[2:])      # Get a slice from index 2 to the end; prints \"[2,3,4]\"\n",
    "print(nums[:2])     # Get a slice from the start to index 2 (exclusive); prints \"[0,1]\"\n",
    "#print(nums[:])      # Get a slice of the whole list; prints [\"0,1,2,3,4\"]\n",
    "#print(nums[:-1])    # slice indices can be negative; prints [0,1,2,3]\n",
    "#nums[2:4] = [8,9]   # Assign a new sublist to a slice\n",
    "#print(nums)          # Prints \"[0,1,8,9,4]\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cat\n",
      "dog\n",
      "monkey\n"
     ]
    }
   ],
   "source": [
    "# Loops\n",
    "animals = ['cat','dog','monkey']\n",
    "for animal in animals:\n",
    "    print (animal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#1: cat\n",
      "#2: dog\n",
      "#3: monkey\n"
     ]
    }
   ],
   "source": [
    "# If we want to access to the index of each element within the body of a loop. use the built-in enumerate function:\n",
    "animals = ['cat','dog','monkey']\n",
    "for idx, animal in enumerate(animals):\n",
    "    print('#%d: %s' %(idx+1, animal))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 4, 9, 16]\n",
      "[0, 1, 4, 9, 16]\n"
     ]
    }
   ],
   "source": [
    "# List comprehensions: When programming, frequently we want to transform one type of data into another. As a \n",
    "# simple example, consider the following:\n",
    "nums = [0,1,2,3,4]\n",
    "squares = []\n",
    "for x in nums: \n",
    "    squares.append(x**2)\n",
    "print(squares)\n",
    "# you can make this code simpler using a list comprehension:\n",
    "nums = [0,1,2,3,4]\n",
    "squares = [x**2 for x in nums]\n",
    "print (squares)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 4, 16]\n"
     ]
    }
   ],
   "source": [
    "nums = [0,1,2,3,4] \n",
    "even_squares = [x**2 for x in nums if x%2 == 0] \n",
    "print(even_squares)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cute\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# Dictionaries : A dictionary stores (key,value) pairs, similar to a Map in JAVA or an object in Javascript\n",
    "d = {'cat':'cute','dog':'furry'} # Create a new dictionary with some data\n",
    "print(d['cat'])                  # Get an entry from a dictionary, prints \"cute\"\n",
    "print('cat' in d)                # Check if dictionary has a given key; prints \"True\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'monkey' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-37-4d77223504ed>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmonkey\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m     \u001b[1;31m# KeyError: 'monkey' not a key of d\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'monkey' is not defined"
     ]
    }
   ],
   "source": [
    "print(d[monkey])     # KeyError: 'monkey' not a key of d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "N/A\n",
      "wet\n",
      "{'dog': 'furry', 'cat': 'cute'}\n"
     ]
    }
   ],
   "source": [
    "print(d.get('monkey','N/A'))   # Get an element with a default; prints \"N/A\"\n",
    "print(d.get('fish','wet'))           # Get an element with a default; prints \"wet\"\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'fish'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-42-a04978364b1f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mdel\u001b[0m \u001b[0md\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'fish'\u001b[0m\u001b[1;33m]\u001b[0m      \u001b[1;31m# Remove an element from a dictionary\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'fish'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'N/A'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# 'fish' is no longer a key; prints \"N/A\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'fish'"
     ]
    }
   ],
   "source": [
    "del d['fish']      # Remove an element from a dictionary\n",
    "print(d.get('fish','N/A')) # 'fish' is no longer a key; prints \"N/A\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'dict' object has no attribute 'iteritems'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-45-76b5d387da60>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# It is easy to iterate over the keys in a dictionary:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0md\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;34m'person'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'cat'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'spider'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m8\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[1;32mfor\u001b[0m \u001b[0manimal\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlegs\u001b[0m \u001b[1;32min\u001b[0m \u001b[0md\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miteritems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'A %s has %d legs'\u001b[0m\u001b[1;33m%\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0manimal\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mlegs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'dict' object has no attribute 'iteritems'"
     ]
    }
   ],
   "source": [
    "# It is easy to iterate over the keys in a dictionary:\n",
    "d = {'person':2,'cat':4,'spider':8}\n",
    "for animal,legs in d.iteritems():\n",
    "    print('A %s has %d legs'%(animal,legs)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 0, 2: 4, 4: 16}\n"
     ]
    }
   ],
   "source": [
    "nums = [0,1,2,3,4]\n",
    "even_num_square = {x:x**2 for x in nums if x % 2 == 0}\n",
    "print(even_num_square)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "#sets A set is a collection of distinct elements. As a simple example, consider the following:\n",
    "animals = {'cat','dog'}\n",
    "print('cat' in animals)   # check if an element is in a set; prints \"True\"\n",
    "print('fish' in animals)  # prints False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "3\n"
     ]
    }
   ],
   "source": [
    "animals.add('fish')    # Add an element to a set\n",
    "print('fish'in animals)\n",
    "print(len(animals))    # Number of elements in a set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "2\n"
     ]
    }
   ],
   "source": [
    "animals.add('cat')  # Adding an element that is already in the set does nothing\n",
    "print(len(animals))\n",
    "animals.remove('dog') # removing an element that is already in the set\n",
    "print(len(animals))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#1: dog\n",
      "#2: fish\n",
      "#3: cat\n"
     ]
    }
   ],
   "source": [
    "# Loops: iterating over a set has the same syntax as iterating over a list; however since sets are unordered\n",
    "# you cannot make assumptions about the order in which you can visit the elements of the set:\n",
    "animals = {'cat','dog','fish'}\n",
    "for idx,animal in enumerate(animals):\n",
    "    print('#%d: %s'%(idx+1, animal))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 1, 2, 3, 4, 5}\n"
     ]
    }
   ],
   "source": [
    "# set comprehensions:like lists and dictionaries, we can easily construct sets using set comprehensions\"\n",
    "from math import sqrt\n",
    "print({int(sqrt(x)) for x in range(30)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tuple'>\n",
      "5\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "# Tuples A Tuple is an (immutable) ordered list of values. A tuple is in many ways similar to a list; \n",
    "# one of the most important differences is that tuples can be used as keys in dictionaries and as elements if sets,\n",
    "# while lists cannot. \n",
    "d = {(x,x + 1): x for x in range(10)} #Create a dictionary with tuple keys\n",
    "t = (5,6)  # Create a Tuple\n",
    "print(type(t))\n",
    "print(d[t])\n",
    "print(d[(1,2)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'tuple' object does not support item assignment",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-57-9c0b399baae2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Tuples cannnot be change unlike lists\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mt\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
     ]
    }
   ],
   "source": [
    "# Tuples cannnot be change unlike lists\n",
    "t[0] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "negative\n",
      "zero\n",
      "positive\n"
     ]
    }
   ],
   "source": [
    "# Functions\n",
    "def sign(x):\n",
    "    if x > 0:\n",
    "        return 'positive'\n",
    "    elif x < 0:\n",
    "        return 'negative'\n",
    "    else:\n",
    "        return 'zero'\n",
    "    \n",
    "for x in [-1,0,1]:\n",
    "    print(sign(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, Bob!\n",
      "HELLO, FRED\n"
     ]
    }
   ],
   "source": [
    "# We will often define functions to take optional keywords arguments, like this:\n",
    "def hello(name, loud = False):\n",
    "    if loud:\n",
    "        print('HELLO, %s' % name.upper())\n",
    "    else:\n",
    "        print('Hello, %s!'%name)\n",
    "hello('Bob')\n",
    "hello('Fred', loud = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, Fred\n",
      "HELLO, FRED!\n"
     ]
    }
   ],
   "source": [
    "# The syntax for defininf classes in Python is straightforward:\n",
    "class Greeter:\n",
    "    \n",
    "    # constructor\n",
    "    def __init__(self, name):\n",
    "        self.name = name # create an instance variable\n",
    "    \n",
    "    # Instance method\n",
    "    def greet(self, loud = False):\n",
    "        if loud:\n",
    "            print('HELLO, %s!' % self.name.upper())\n",
    "        else:\n",
    "            print('Hello, %s' % self.name)\n",
    "g = Greeter('Fred')  # Construct an instance of the greeter class\n",
    "g.greet()            # Call an instance method; prints \"Hello, Fred\"\n",
    "g.greet(loud=True)   # Call an instance method; prints \"HELLO,FRED!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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