mirror of
https://github.com/gsi-upm/sitc
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348 lines
6.8 KiB
Plaintext
348 lines
6.8 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, © 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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"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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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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"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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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": null,
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"metadata": {},
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"outputs": [],
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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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"© Carlos A. Iglesias, Universidad Politécnica de Madrid."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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},
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"latex_envs": {
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"LaTeX_envs_menu_present": true,
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"autocomplete": true,
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"bibliofile": "biblio.bib",
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"cite_by": "apalike",
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"current_citInitial": 1,
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"eqLabelWithNumbers": true,
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"eqNumInitial": 1,
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"hotkeys": {
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"equation": "Ctrl-E",
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"itemize": "Ctrl-I"
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},
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"labels_anchors": false,
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"latex_user_defs": false,
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"report_style_numbering": false,
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"user_envs_cfg": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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