mirror of
https://github.com/donnemartin/data-science-ipython-notebooks.git
synced 2024-03-22 13:30:56 +08:00
819 lines
16 KiB
Plaintext
819 lines
16 KiB
Plaintext
{
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"metadata": {
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"name": "",
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"signature": "sha256:f24f6112f8e8e28d262a4f84be84d1ae459154a9a445687d55392ff177e6a03c"
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},
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"nbformat": 3,
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"nbformat_minor": 0,
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"worksheets": [
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Data Structures"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## tuple"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# One dimensional, fixed-length, immutable sequence\n",
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"tup = (1, 2, 3)\n",
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"tup"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 1,
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"text": [
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"(1, 2, 3)"
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]
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}
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],
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"prompt_number": 1
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"a_list = [1, 2, 3]"
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],
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"language": "python",
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"metadata": {},
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"outputs": [],
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"prompt_number": 2
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Convert to a tuple\n",
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"type(tuple(a_list))"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 3,
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"text": [
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"tuple"
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]
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}
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],
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"prompt_number": 3
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Nested tuples\n",
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"nested_tup = ([1, 2, 3], (4, 5))\n",
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"nested_tup"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 4,
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"text": [
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"([1, 2, 3], (4, 5))"
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]
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}
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],
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"prompt_number": 4
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Access by index O(1)\n",
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"nested_tup[0]"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 5,
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"text": [
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"[1, 2, 3]"
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]
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}
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],
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"prompt_number": 5
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Although tuples are immutable, their contents can contain mutable objects\n",
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"nested_tup[0].append(4)\n",
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"nested_tup[0]"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
|
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 6,
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"text": [
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"[1, 2, 3, 4]"
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]
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}
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],
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"prompt_number": 6
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Concatenate tuples\n",
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"# Creates a new tuple and copies objects\n",
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"(1, 3, 2) + (4, 5, 6)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 7,
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"text": [
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"(1, 3, 2, 4, 5, 6)"
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]
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}
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],
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"prompt_number": 7
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Multiply copies references to objects (objects themselves are not copied)\n",
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"('foo', 'bar') * 2"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 8,
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"text": [
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"('foo', 'bar', 'foo', 'bar')"
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]
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}
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],
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"prompt_number": 8
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Unpack tuples\n",
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"a, b = nested_tup\n",
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"a, b"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 9,
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"text": [
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"([1, 2, 3, 4], (4, 5))"
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]
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}
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],
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"prompt_number": 9
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Unpack nested tuples\n",
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"(a, b, c, d), (e, f) = nested_tup\n",
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"a, b, c, d, e, f"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 10,
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"text": [
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"(1, 2, 3, 4, 4, 5)"
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]
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}
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],
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"prompt_number": 10
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# A common use of variable unpacking is when iterating over sequences\n",
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"# of tuples or lists\n",
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"seq = [( 1, 2, 3), (4, 5, 6), (7, 8, 9)] \n",
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"for a, b, c in seq: \n",
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" print(a, b, c)"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"output_type": "stream",
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"stream": "stdout",
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"text": [
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"(1, 2, 3)\n",
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"(4, 5, 6)\n",
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"(7, 8, 9)\n"
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]
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}
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],
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"prompt_number": 11
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## list"
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]
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
|
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"# One dimensional, variable-length, mutable sequence\n",
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"a_list = [1, 2, 3]\n",
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"a_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
|
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 12,
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"text": [
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"[1, 2, 3]"
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]
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}
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],
|
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"prompt_number": 12
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
|
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"# Convert to a list\n",
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"type(list(tup))"
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],
|
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"language": "python",
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"metadata": {},
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"outputs": [
|
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 13,
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"text": [
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"list"
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]
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}
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],
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"prompt_number": 13
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Nested list\n",
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"nested_list = [(1, 2, 3), [4, 5]]\n",
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"nested_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 14,
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"text": [
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"[(1, 2, 3), [4, 5]]"
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]
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}
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],
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"prompt_number": 14
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
|
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"# Access by index\n",
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"nested_list[1]"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 15,
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"text": [
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"[4, 5]"
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]
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}
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],
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"prompt_number": 15
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Append an element O(1)\n",
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"nested_list.append(6)\n",
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"nested_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 16,
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"text": [
|
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"[(1, 2, 3), [4, 5], 6]"
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]
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}
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],
|
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"prompt_number": 16
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},
|
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{
|
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"cell_type": "code",
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"collapsed": false,
|
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"input": [
|
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"# Insert an element at a specific index\n",
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"# Insert is expensive as it has to shift subsequent elements O(n)\n",
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"nested_list.insert(0, 'start')\n",
|
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"nested_list"
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],
|
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"language": "python",
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"metadata": {},
|
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"outputs": [
|
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 17,
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"text": [
|
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"['start', (1, 2, 3), [4, 5], 6]"
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]
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}
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],
|
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"prompt_number": 17
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
|
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"# Pop removes and returns an element from a specified index\n",
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"# Pop is expensive as it has to shift subsequent elements O(n)\n",
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"# O(1) if pop is used for the last element\n",
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"nested_list.pop(0)\n",
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"nested_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 18,
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"text": [
|
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"[(1, 2, 3), [4, 5], 6]"
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]
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}
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],
|
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"prompt_number": 18
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
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"# Remove locates the first such value and removes it O(n)\n",
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"nested_list.remove((1, 2, 3))\n",
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"nested_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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"metadata": {},
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"output_type": "pyout",
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"prompt_number": 19,
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"text": [
|
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"[[4, 5], 6]"
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]
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}
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],
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"prompt_number": 19
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},
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{
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"cell_type": "code",
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"collapsed": false,
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"input": [
|
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"# Check if a list contains a value O(n)\n",
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"6 in nested_list"
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],
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"language": "python",
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"metadata": {},
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"outputs": [
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{
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|
"metadata": {},
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"output_type": "pyout",
|
|
"prompt_number": 20,
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"text": [
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"True"
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]
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}
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],
|
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"prompt_number": 20
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},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
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"# Concatenate lists\n",
|
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"# Creates a new list and copies objects\n",
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"[1, 3, 2] + [4, 5, 6]"
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],
|
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"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
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{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 21,
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"text": [
|
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"[1, 3, 2, 4, 5, 6]"
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]
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}
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],
|
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"prompt_number": 21
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},
|
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{
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"cell_type": "code",
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"collapsed": false,
|
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"input": [
|
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"# Extend a list by appending elements\n",
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"# Faster than concatenating lists\n",
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"nested_list.extend([7, 8, 9])\n",
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"nested_list"
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],
|
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"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
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{
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|
"metadata": {},
|
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"output_type": "pyout",
|
|
"prompt_number": 22,
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|
"text": [
|
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"[[4, 5], 6, 7, 8, 9]"
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]
|
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}
|
|
],
|
|
"prompt_number": 22
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},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
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"## sort"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
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"# Sort in-place O(n log n)\n",
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"a_list = [1, 5, 3, 9, 7, 6]\n",
|
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"a_list.sort()\n",
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"a_list"
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],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 23,
|
|
"text": [
|
|
"[1, 3, 5, 6, 7, 9]"
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|
]
|
|
}
|
|
],
|
|
"prompt_number": 23
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"# Sort by secondary key: str length\n",
|
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"b_list = ['the', 'quick', 'brown', 'fox', 'jumps', 'over']\n",
|
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"b_list.sort(key=len)\n",
|
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"b_list"
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|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 24,
|
|
"text": [
|
|
"['the', 'fox', 'over', 'quick', 'brown', 'jumps']"
|
|
]
|
|
}
|
|
],
|
|
"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",
|
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"\n",
|
|
"# Find the location where an element should be inserted to keep the\n",
|
|
"# list sorted\n",
|
|
"c_list = [1, 2, 2, 3, 5, 13]\n",
|
|
"bisect.bisect(c_list, 8)"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 25,
|
|
"text": [
|
|
"5"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 25
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"collapsed": false,
|
|
"input": [
|
|
"# Inserts an element into a location to keep the list sorted\n",
|
|
"bisect.insort(c_list, 8)\n",
|
|
"c_list"
|
|
],
|
|
"language": "python",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"metadata": {},
|
|
"output_type": "pyout",
|
|
"prompt_number": 26,
|
|
"text": [
|
|
"[1, 2, 2, 3, 5, 8, 13]"
|
|
]
|
|
}
|
|
],
|
|
"prompt_number": 26
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## slice"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
""
|
|
]
|
|
},
|
|
{
|
|
"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": {}
|
|
}
|
|
]
|
|
} |