data-science-ipython-notebooks/core/structs.ipynb

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{
"metadata": {
"name": "",
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"signature": "sha256:f24f6112f8e8e28d262a4f84be84d1ae459154a9a445687d55392ff177e6a03c"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Data Structures"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
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"## tuple"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# One dimensional, fixed-length, immutable sequence\n",
"tup = (1, 2, 3)\n",
"tup"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 1,
"text": [
"(1, 2, 3)"
]
}
],
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"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a_list = [1, 2, 3]"
],
"language": "python",
"metadata": {},
"outputs": [],
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"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Convert to a tuple\n",
"type(tuple(a_list))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 3,
"text": [
"tuple"
]
}
],
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"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Nested tuples\n",
"nested_tup = ([1, 2, 3], (4, 5))\n",
"nested_tup"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 4,
"text": [
"([1, 2, 3], (4, 5))"
]
}
],
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"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Access by index O(1)\n",
"nested_tup[0]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 5,
"text": [
"[1, 2, 3]"
]
}
],
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"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Although tuples are immutable, their contents can contain mutable objects\n",
"nested_tup[0].append(4)\n",
"nested_tup[0]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 6,
"text": [
"[1, 2, 3, 4]"
]
}
],
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"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Concatenate tuples\n",
"# Creates a new tuple and copies objects\n",
"(1, 3, 2) + (4, 5, 6)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 7,
"text": [
"(1, 3, 2, 4, 5, 6)"
]
}
],
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"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Multiply copies references to objects (objects themselves are not copied)\n",
"('foo', 'bar') * 2"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 8,
"text": [
"('foo', 'bar', 'foo', 'bar')"
]
}
],
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"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Unpack tuples\n",
"a, b = nested_tup\n",
"a, b"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 9,
"text": [
"([1, 2, 3, 4], (4, 5))"
]
}
],
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"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Unpack nested tuples\n",
"(a, b, c, d), (e, f) = nested_tup\n",
"a, b, c, d, e, f"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 10,
"text": [
"(1, 2, 3, 4, 4, 5)"
]
}
],
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"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# A common use of variable unpacking is when iterating over sequences\n",
"# of tuples or lists\n",
"seq = [( 1, 2, 3), (4, 5, 6), (7, 8, 9)] \n",
"for a, b, c in seq: \n",
" print(a, b, c)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(1, 2, 3)\n",
"(4, 5, 6)\n",
"(7, 8, 9)\n"
]
}
],
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"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
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"## list"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# One dimensional, variable-length, mutable sequence\n",
"a_list = [1, 2, 3]\n",
"a_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 12,
"text": [
"[1, 2, 3]"
]
}
],
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"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Convert to a list\n",
"type(list(tup))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 13,
"text": [
"list"
]
}
],
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"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Nested list\n",
"nested_list = [(1, 2, 3), [4, 5]]\n",
"nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 14,
"text": [
"[(1, 2, 3), [4, 5]]"
]
}
],
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"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Access by index\n",
"nested_list[1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 15,
"text": [
"[4, 5]"
]
}
],
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"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Append an element O(1)\n",
"nested_list.append(6)\n",
"nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 16,
"text": [
"[(1, 2, 3), [4, 5], 6]"
]
}
],
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"prompt_number": 16
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Insert an element at a specific index\n",
"# Insert is expensive as it has to shift subsequent elements O(n)\n",
"nested_list.insert(0, 'start')\n",
"nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 17,
"text": [
"['start', (1, 2, 3), [4, 5], 6]"
]
}
],
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"prompt_number": 17
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Pop removes and returns an element from a specified index\n",
"# Pop is expensive as it has to shift subsequent elements O(n)\n",
"# O(1) if pop is used for the last element\n",
"nested_list.pop(0)\n",
"nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 18,
"text": [
"[(1, 2, 3), [4, 5], 6]"
]
}
],
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"prompt_number": 18
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Remove locates the first such value and removes it O(n)\n",
"nested_list.remove((1, 2, 3))\n",
"nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 19,
"text": [
"[[4, 5], 6]"
]
}
],
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"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Check if a list contains a value O(n)\n",
"6 in nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 20,
"text": [
"True"
]
}
],
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"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Concatenate lists\n",
"# Creates a new list and copies objects\n",
"[1, 3, 2] + [4, 5, 6]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 21,
"text": [
"[1, 3, 2, 4, 5, 6]"
]
}
],
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"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Extend a list by appending elements\n",
"# Faster than concatenating lists\n",
"nested_list.extend([7, 8, 9])\n",
"nested_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 22,
"text": [
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"[[4, 5], 6, 7, 8, 9]"
]
}
],
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"prompt_number": 22
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## sort"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Sort in-place O(n log n)\n",
"a_list = [1, 5, 3, 9, 7, 6]\n",
"a_list.sort()\n",
"a_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 23,
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"text": [
"[1, 3, 5, 6, 7, 9]"
]
}
],
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"prompt_number": 23
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},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Sort by secondary key: str length\n",
"b_list = ['the', 'quick', 'brown', 'fox', 'jumps', 'over']\n",
"b_list.sort(key=len)\n",
"b_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 24,
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"text": [
"['the', 'fox', 'over', 'quick', 'brown', 'jumps']"
]
}
],
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"prompt_number": 24
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## bisect"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# The bisect module does not check whether the list is sorted, as this check\n",
"# would be expensive O(n). Using bisect on an unsorted list will not result\n",
"# in an error but could lead to incorrect results.\n",
"import bisect\n",
"\n",
"# Find the location where an element should be inserted to keep the\n",
"# list sorted\n",
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"c_list = [1, 2, 2, 3, 5, 13]\n",
"bisect.bisect(c_list, 8)"
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],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 25,
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"text": [
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"5"
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]
}
],
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"prompt_number": 25
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},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Inserts an element into a location to keep the list sorted\n",
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"bisect.insort(c_list, 8)\n",
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"c_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
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"prompt_number": 26,
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"text": [
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"[1, 2, 2, 3, 5, 8, 13]"
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]
}
],
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"prompt_number": 26
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## slice"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![alt text](http://www.nltk.org/images/string-slicing.png)"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Select a section of list types (arrays, tuples, NumPy arrays)\n",
"# start:stop\n",
"# start is included, stop is not\n",
"# number of elements in the result is stop - start\n",
"d_list = 'Monty Python'\n",
"d_list[6:10]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 27,
"text": [
"'Pyth'"
]
}
],
"prompt_number": 27
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Omit start to default to start of the sequence\n",
"d_list[:5]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 28,
"text": [
"'Monty'"
]
}
],
"prompt_number": 28
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Omit end to default to end of the sequence\n",
"d_list[6:]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 29,
"text": [
"'Python'"
]
}
],
"prompt_number": 29
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Negative indices slice relative to the end\n",
"d_list[-12:-7]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 30,
"text": [
"'Monty'"
]
}
],
"prompt_number": 30
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Slice can also take a step such as the one below, which takes\n",
"# every other element\n",
"e_list[::2]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 33,
"text": [
"[1, 2, 5, 13]"
]
}
],
"prompt_number": 33
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Passing -1 for the step reverses the list or tuple:\n",
"e_list[::-1]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 34,
"text": [
"[13, ['H', 'a', 'l', 'l'], 5, 3, 2, 1, 1]"
]
}
],
"prompt_number": 34
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Assign elements to a slice\n",
"# Slice range does not have to equal number of elements to assign\n",
"e_list = [1, 1, 2, 3, 5, 8, 13]\n",
"e_list[5:] = ['H', 'a', 'l', 'l']\n",
"e_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 31,
"text": [
"[1, 1, 2, 3, 5, 'H', 'a', 'l', 'l']"
]
}
],
"prompt_number": 31
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Compare assigning into a slice (above) versus assigning into\n",
"# an inde\n",
"e_list"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 32,
"text": [
"[1, 1, 2, 3, 5, ['H', 'a', 'l', 'l'], 13]"
]
}
],
"prompt_number": 32
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}