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      "<center><h1>Introduction to Python</h1><br>\n",
      "<h2>Christof Angermueller</h2>\n",
      "<h2><a href=\"http://twitter.com/cangermueller\">@cangermueller</a></h2>\n",
      "<h2><a href=\"http://cangermueller.com\">http://cangermueller.com</a></h2>\n",
      "<h2><a href=\"http://goo.gl/cAU9Tq\">http://goo.gl/cAU9Tq</a></h2>\n",
      "</center>"
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     "cell_type": "heading",
     "level": 1,
     "metadata": {
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       "slide_type": "slide"
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     "source": [
      "About me"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Studies 2008-2013"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img  src='figures/me_studies.png' align='center'/>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "PhD 2014-"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {
      "slideshow": {
       "slide_type": "-"
      }
     },
     "source": [
      "<img src='figures/me_ebi.png' align='center'/>"
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    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "Why Python?"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src='figures/python.png' align='center' width=30%/>\n",
      "* Increasing popularity\n",
      "* Good trade-off performance vs. productivity\n",
      "* [IPython for interactive computing](http://ipython.org/)\n",
      "* Many packages\n",
      "\n",
      "\n",
      "* [Python for R users](http://mathesaurus.sourceforge.net/r-numpy.html)\n",
      "* [Python for matlab users](http://www.pyzo.org/python_vs_matlab.html)"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "Increasing popularity"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src='figures/languages.png' align='center'/>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "Good trade-off performance vs. productivity"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src='figures/performance_productivity.png' align='center'/>"
     ]
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    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
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     },
     "source": [
      "Many packages"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<img src='figures/packages.png' align='center'/>"
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     "cell_type": "heading",
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     "source": [
      "Fundamental types"
     ]
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     "input": [
      "a = 10\n",
      "a"
     ],
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        "int"
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      "a = 1.0\n",
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       "metadata": {},
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        "1.0"
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     "cell_type": "code",
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     "input": [
      "a = 1 / 2\n",
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      {
       "metadata": {},
       "output_type": "pyout",
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        "0.5"
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     "cell_type": "code",
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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "float"
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     "prompt_number": 8
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    {
     "cell_type": "code",
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     "input": [
      "s = 'Hello world!'\n",
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     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "'Hello world!'"
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     "cell_type": "code",
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       "metadata": {},
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       "prompt_number": 10,
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        "12"
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "'e'"
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     ],
     "prompt_number": 13
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "'Foo' + 'Bar'"
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     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "'FooBar'"
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     "cell_type": "heading",
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     "source": [
      "list"
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l = [1, 2, 3]\n",
      "l"
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        "list"
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     "collapsed": false,
     "input": [
      "l = list(range(1, 10))\n",
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
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        "[1, 2, 3, 4, 5, 6, 7, 8, 9]"
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     "cell_type": "code",
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      "len(l)"
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "9"
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     "prompt_number": 19
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     "cell_type": "code",
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      "l[-1]"
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       "metadata": {},
       "output_type": "pyout",
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        "9"
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     "prompt_number": 20
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     "cell_type": "code",
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     "input": [
      "l[:5]"
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     "language": "python",
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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
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        "[1, 2, 3, 4, 5]"
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     "prompt_number": 21
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l[5:]"
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     "language": "python",
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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
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        "[6, 7, 8, 9]"
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     "prompt_number": 22
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     "cell_type": "code",
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       "metadata": {},
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        "[1, 3, 5, 7, 9]"
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     "prompt_number": 24
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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
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     "prompt_number": 25
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l.append([10, 11, 12])\n",
      "l"
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     "language": "python",
     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "[1, 2, 3, 4, 5, 6, 7, 8, 9, [10, 11, 12]]"
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     "prompt_number": 26
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l[-1]"
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     "language": "python",
     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "[10, 11, 12]"
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      }
     ],
     "prompt_number": 27
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l.extend([13, 14, 15])\n",
      "l"
     ],
     "language": "python",
     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "[1, 2, 3, 4, 5, 6, 7, 8, 9, [10, 11, 12], 13, 14, 15, 13, 14, 15]"
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      }
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     "prompt_number": 29
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l = range(100000)"
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     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
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     "source": [
      "dict"
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "d = {'a': 1, 'b':2, 'c': 3}\n",
      "d"
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     "language": "python",
     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "{'c': 3, 'a': 1, 'b': 2}"
       ]
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     "prompt_number": 30
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     "cell_type": "code",
     "collapsed": false,
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      "type(d)"
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       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "dict"
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     "prompt_number": 31
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "d['a']"
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     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "1"
       ]
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     ],
     "prompt_number": 32
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "d.keys()"
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     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 33,
       "text": [
        "dict_keys(['c', 'a', 'b'])"
       ]
      }
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     "prompt_number": 33
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "d.values()"
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     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "dict_values([3, 1, 2])"
       ]
      }
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     "prompt_number": 34
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for k, v in d.items():\n",
      "    print(k, v)"
     ],
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     "outputs": [
      {
       "output_type": "stream",
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       "text": [
        "c 3\n",
        "a 1\n",
        "b 2\n"
       ]
      }
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     "prompt_number": 36
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    {
     "cell_type": "heading",
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      "set"
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      "s = {'a', 'b', 'c', 'c'}\n",
      "s"
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       "metadata": {},
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       "text": [
        "{'a', 'b', 'c'}"
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     "prompt_number": 37
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "type(s)"
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     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 39,
       "text": [
        "set"
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     "prompt_number": 39
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "'s' in s"
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       "metadata": {},
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       "prompt_number": 40,
       "text": [
        "False"
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     "prompt_number": 40
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     "cell_type": "code",
     "collapsed": false,
     "input": [
      "s.union({'a', 'b', 'f'})"
     ],
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      {
       "metadata": {},
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       "prompt_number": 41,
       "text": [
        "{'a', 'b', 'c', 'f'}"
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     "prompt_number": 41
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    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
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     },
     "source": [
      "Loops and comprehensions"
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    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def square_loop(l):\n",
      "    rv = []\n",
      "    for v in l:\n",
      "        rv.append(v**2)\n",
      "    return rv"
     ],
     "language": "python",
     "metadata": {
      "slideshow": {
       "slide_type": "-"
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     },
     "outputs": [],
     "prompt_number": 42
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "square_loop(range(5))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 44,
       "text": [
        "[0, 1, 4, 9, 16]"
       ]
      }
     ],
     "prompt_number": 44
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def square_comprehension(l):\n",
      "    return [v**2 for v in l]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 45
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "square_comprehension(range(5))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 46,
       "text": [
        "[0, 1, 4, 9, 16]"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "l = range(100000)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit square_loop(l)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 46.3 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%timeit square_comprehension(l)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "10 loops, best of 3: 41.3 ms per loop\n"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
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     },
     "source": [
      "Importing packages"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "math.pi"
     ],
     "language": "python",
     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 54,
       "text": [
        "3.141592653589793"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "math.sqrt(2)"
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     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 55,
       "text": [
        "1.4142135623730951"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "math.exp(1)"
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     "language": "python",
     "metadata": {},
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      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 56,
       "text": [
        "2.718281828459045"
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     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "math.log(math.e)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 57,
       "text": [
        "1.0"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {
      "slideshow": {
       "slide_type": "slide"
      }
     },
     "source": [
      "Further readings"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "* [Python basics notebook](http://nbviewer.ipython.org/github/jrjohansson/scientific-python-lectures/blob/master/Lecture-1-Introduction-to-Python-Programming.ipynb)\n",
      "* http://www.python.org - The official web page of the Python programming language.\n",
      "* http://www.python.org/dev/peps/pep-0008 - Style guide for Python programming. Highly recommended. \n",
      "* http://ipython.org - The official IPython web page with further information about IPython notebook and IPython console \n"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}