mirror of
https://github.com/gsi-upm/sitc
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625 lines
11 KiB
Plaintext
625 lines
11 KiB
Plaintext
{
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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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"![](http://www.upm.es/sfs/Rectorado/Gabinete%20del%20Rector/Logos/UPM/EscPolitecnica/EscUpmPolit_p.gif \"UPM\")"
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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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"# Course Notes for Learning Intelligent Systems"
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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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"Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © 2015 Carlos A. Iglesias"
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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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"# Built-in Types: Sets and Mappings"
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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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"* *Sets* are unordered bags of values\n",
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"* *Dictionaries* are unordered bags of key-values pairs\n",
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"\n",
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"A set object is an unordered collection of distinct objects. There are two built-in set types: **set** (mutable) and **frozenset** (inmutable).\n",
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"\n",
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"A mapping object maps hashable values to arbitrary objects. Mappings are mutable objects. There is only one bultin mapping type: **dictionary**."
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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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"collapsed": true
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},
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"source": [
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"## 1. Sets"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 413,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"set()"
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]
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},
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"execution_count": 413,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_set = set() #create a set\n",
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"my_set"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 414,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{1}"
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]
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},
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"execution_count": 414,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_set.add(1) # add an element\n",
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"my_set"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 415,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"my_set.add(2) # add another element"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 416,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{1, 2}"
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]
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},
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"execution_count": 416,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_set"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 417,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{1, 2, 3}"
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]
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},
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"execution_count": 417,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_set.add(3) # add another one\n",
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"my_set"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 418,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{1, 2, 3}"
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]
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},
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"execution_count": 418,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_set.add(1) #try to add a repeated element\n",
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"my_set"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 419,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{0, 1, 2, 3, 4, 5, 6, 7, 8, 9}"
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]
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},
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"execution_count": 419,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"s2 = set(range(10)) # we can create a set from a range\n",
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"s2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 420,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"l = ['a', 'a', 'b', 'c', 'c', 'c']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 421,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'a', 'b', 'c'}"
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]
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},
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"execution_count": 421,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"s3 = set(l) # if we create a set from a list, elements are not repeated\n",
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"s3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 422,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"3"
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]
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},
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"execution_count": 422,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(s3) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 423,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{0, 1, 2, 3, 4, 5, 'c', 6, 7, 8, 9, 'a', 'b'}"
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]
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},
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"execution_count": 423,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"s3.union(s2) # we can use set methods: union(), intersection(), difference(), ..."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 424,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 424,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"3 in my_set #check membership"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 425,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"set"
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]
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},
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"execution_count": 425,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"type(s3)"
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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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"## 2. Dictionaries"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 426,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'key1': 1, 'key2': 2, 'key3': 3}"
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]
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},
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"execution_count": 426,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dictionary = {'key1': 1, 'key2': 2, 'key3': 3} # pairs of key-value mappings\n",
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"my_dictionary"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 427,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1"
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]
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},
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"execution_count": 427,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dictionary['key1'] #retrieve a value given a key"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 428,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'key1': 1, 'key2': 2, 'key3': 3}"
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]
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},
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"execution_count": 428,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dict = dict()\n",
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"my_dict['key1'] = 1\n",
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"my_dict['key2'] = 2\n",
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"my_dict['key3'] = 3\n",
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"my_dict # alternative way to create a dictionary "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 429,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"True"
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]
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},
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"execution_count": 429,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dict == my_dictionary # check if both dictionaries are equal"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 430,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'one': {'two': {'three': 'Nested dict'}}}"
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]
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},
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"execution_count": 430,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dict2 = {'one': {'two': {'three': 'Nested dict'}}} #nested dictionary\n",
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"my_dict2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 431,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'Nested dict'"
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]
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},
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"execution_count": 431,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dict2['one']['two']['three'] #access the value"
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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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"collapsed": false
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},
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"source": [
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"Dictionaries have different methods, check them with Tab."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 473,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"dict_keys(['key2', 'key3', 'key1'])"
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]
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},
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"execution_count": 473,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dict.keys() # in Python3 we get a View object that changes when the dictionary changes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 478,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['key2', 'key3', 'key1']"
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]
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},
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"execution_count": 478,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"list(my_dict.keys()) # we can convert it to a list, we see dicionaries are unordered"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 474,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"dict_values([2, 3, 1])"
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]
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},
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"execution_count": 474,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_dict.values()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 476,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[2, 3, 1]"
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]
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},
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"execution_count": 476,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"list(my_dict.values())"
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]
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},
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{
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"cell_type": "code",
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|
"execution_count": 479,
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|
"metadata": {
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|
"collapsed": false
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},
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"outputs": [
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{
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|
"data": {
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|
"text/plain": [
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"dict"
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|
]
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|
},
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|
"execution_count": 479,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"type(my_dict)"
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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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"# Licence"
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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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"The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
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"\n",
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"© 2015 Carlos A. Iglesias, Universidad Politécnica de Madrid."
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|
]
|
|
}
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|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
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|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
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|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.4.3+"
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|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
}
|