00-Python Object and Data Structure Basics/.ipynb_checkpoints/05-Dictionaries-checkpoint.ipynb

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    "___\n",
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    "___\n",
    "<center><em>Content Copyright by Pierian Data</em></center>"
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   "source": [
    "# Dictionaries\n",
    "\n",
    "We've been learning about *sequences* in Python but now we're going to switch gears and learn about *mappings* in Python. If you're familiar with other languages you can think of these Dictionaries as hash tables. \n",
    "\n",
    "This section will serve as a brief introduction to dictionaries and consist of:\n",
    "\n",
    "    1.) Constructing a Dictionary\n",
    "    2.) Accessing objects from a dictionary\n",
    "    3.) Nesting Dictionaries\n",
    "    4.) Basic Dictionary Methods\n",
    "\n",
    "So what are mappings? Mappings are a collection of objects that are stored by a *key*, unlike a sequence that stored objects by their relative position. This is an important distinction, since mappings won't retain order since they have objects defined by a key.\n",
    "\n",
    "A Python dictionary consists of a key and then an associated value. That value can be almost any Python object.\n",
    "\n",
    "\n",
    "## Constructing a Dictionary\n",
    "Let's see how we can construct dictionaries to get a better understanding of how they work!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Make a dictionary with {} and : to signify a key and a value\n",
    "my_dict = {'key1':'value1','key2':'value2'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'value2'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Call values by their key\n",
    "my_dict['key2']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Its important to note that dictionaries are very flexible in the data types they can hold. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "my_dict = {'key1':123,'key2':[12,23,33],'key3':['item0','item1','item2']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['item0', 'item1', 'item2']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's call items from the dictionary\n",
    "my_dict['key3']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'item0'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Can call an index on that value\n",
    "my_dict['key3'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ITEM0'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Can then even call methods on that value\n",
    "my_dict['key3'][0].upper()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can affect the values of a key as well. For instance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "123"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_dict['key1']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Subtract 123 from the value\n",
    "my_dict['key1'] = my_dict['key1'] - 123"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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     "execution_count": 9,
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   ],
   "source": [
    "#Check\n",
    "my_dict['key1']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A quick note, Python has a built-in method of doing a self subtraction or addition (or multiplication or division). We could have also used += or -= for the above statement. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-123"
      ]
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     "execution_count": 10,
     "metadata": {},
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   "source": [
    "# Set the object equal to itself minus 123 \n",
    "my_dict['key1'] -= 123\n",
    "my_dict['key1']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also create keys by assignment. For instance if we started off with an empty dictionary, we could continually add to it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a new dictionary\n",
    "d = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a new key through assignment\n",
    "d['animal'] = 'Dog'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Can do this with any object\n",
    "d['answer'] = 42"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'animal': 'Dog', 'answer': 42}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Show\n",
    "d"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nesting with Dictionaries\n",
    "\n",
    "Hopefully you're starting to see how powerful Python is with its flexibility of nesting objects and calling methods on them. Let's see a dictionary nested inside a dictionary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Dictionary nested inside a dictionary nested inside a dictionary\n",
    "d = {'key1':{'nestkey':{'subnestkey':'value'}}}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wow! That's a quite the inception of dictionaries! Let's see how we can grab that value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'value'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Keep calling the keys\n",
    "d['key1']['nestkey']['subnestkey']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A few Dictionary Methods\n",
    "\n",
    "There are a few methods we can call on a dictionary. Let's get a quick introduction to a few of them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a typical dictionary\n",
    "d = {'key1':1,'key2':2,'key3':3}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['key1', 'key2', 'key3'])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Method to return a list of all keys \n",
    "d.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_values([1, 2, 3])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Method to grab all values\n",
    "d.values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_items([('key1', 1), ('key2', 2), ('key3', 3)])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Method to return tuples of all items  (we'll learn about tuples soon)\n",
    "d.items()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hopefully you now have a good basic understanding how to construct dictionaries. There's a lot more to go into here, but we will revisit dictionaries at later time. After this section all you need to know is how to create a dictionary and how to retrieve values from it."
   ]
  }
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