Functions.ipynb

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   "source": [
    "x=12\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x +=2\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#python 2 will not understand that 5/9 is a float and will return first digit onls (0 in this case), one of the numbers has to be a float!\n",
    "def fahr_to_kelvin(temp):\n",
    "    converted = ((temp - 32)*(float(5) / 9) + 273.15)\n",
    "    #or\n",
    "    converted = ((temp - 32)*(5.0 / 9) + 273.15)\n",
    "    return converted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "result = fahr_to_kelvin(1000)\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(fahr_to_kelvin(1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "outputs": [],
   "source": [
    "20/9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def kelvin_to_Celsius(temp_k):\n",
    "    converted = temp_k - 273.15\n",
    "    return converted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "kelvin_to_Celsius(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def fahrenheit_to_Celsius(temp_f):\n",
    "    temp_k= fahr_to_kelvin(temp_f)\n",
    "    result = kelvin_to_Celsius(temp_k)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fahrenheit_to_Celsius(32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def join_words(a, b):\n",
    "    result=a+\" \"+b\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "join_words(\"My name is\", \"Norman\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def outer(z):\n",
    "    a=z[0]\n",
    "    b=z[-1]\n",
    "    result=a+b\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "outer(\"helium\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "my_numbers=[1,2,3,4,5,6,7,8,9]\n",
    "#result multiply everything by 5\n",
    "def sum_numbers(numbers_to_multiply):\n",
    "    new_numbers=[]\n",
    "    for x in numbers_to_multiply:   \n",
    "        new_numbers.append(x)\n",
    "    for x in numbers_to_multiply:   \n",
    "        y = x*5\n",
    "        new_numbers.append(y)\n",
    "    return new_numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 10, 15, 20, 25, 30, 35, 40, 45]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum_numbers(my_numbers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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