01-python-basics.ipynb

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   "cell_type": "code",
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   "source": [
    "import array"
   ]
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   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "Hello world\n"
     ]
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   "source": [
    "print('Hello world')"
   ]
  },
  {
   "cell_type": "markdown",
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    "# Python native data types\n",
    "Python has many native datatypes. Here are the important ones:\n",
    "\n",
    " - **Booleans** are either `True` or `False`.\n",
    " - **Numbers** can be integers (1 and 2), floats (1.1 and 1.2), fractions (1/2 and 2/3), or even complex numbers.\n",
    " - **Strings** are sequences of Unicode characters, e.g. an html document.\n",
    " - **Lists** are ordered sequences of values. Can be different types.\n",
    " - **Arrays** are ordered sequences of values of the same type. The size needs to be predefined.\n",
    " - **Tuples** are ordered, immutable sequences of values.\n",
    " - **Sets** are unordered bags of values.\n",
    " - **Dictionaries** are unordered bags of key-value pairs.\n",
    " \n",
    "See [here](http://www.diveintopython3.net/native-datatypes.html) for a complete overview.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "Hg3_piR5yNdr"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "bool"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = True\n",
    "type(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = \"this is a string\"\n",
    "type(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "[1, 2, 3]\n"
     ]
    }
   ],
   "source": [
    "mylist = [1, 2, 3]\n",
    "print(type(mylist))\n",
    "print(mylist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n",
      "array('i', [3, 6, 9, 12])\n"
     ]
    }
   ],
   "source": [
    "a1 = array.array(\"i\", [3, 6, 9, 12])\n",
    "print(type(a1))\n",
    "print(a1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tuple'>\n",
      "('value', 12)\n"
     ]
    }
   ],
   "source": [
    "my_tuple = ('value', 12)\n",
    "print(type(my_tuple))\n",
    "print(my_tuple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'set'>\n",
      "{1, 2, 3}\n"
     ]
    }
   ],
   "source": [
    "my_set = set([1, 2, 2, 3])\n",
    "print(type(my_set))\n",
    "print(my_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'dict'>\n",
      "{'name': 'test'}\n"
     ]
    }
   ],
   "source": [
    "d = dict()\n",
    "d['name'] = 'test'\n",
    "\n",
    "print(type(d))\n",
    "print(d)"
   ]
  }
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