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‎.ipynb_checkpoints/Advanced Functions Quiz-checkpoint.ipynb

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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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"#Advanced Functions Quiz"
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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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"metadata": {
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"version": 2
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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": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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‎.ipynb_checkpoints/Collections Module-checkpoint.ipynb

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"print d1 == d2"
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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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"#namedtuple\n",
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"The standard tuple uses numerical indexes to access its members, for example:"
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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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"execution_count": 38,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"t = (12,13,14)"
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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": 39,
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"metadata": {
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"collapsed": false
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"outputs": [
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{
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"data": {
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"text/plain": [
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"12"
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]
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},
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"execution_count": 39,
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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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"t[0]"
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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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"For simple use cases, this is usually enough. On the other hand, remembering which index should be used for each value can lead to errors, especially if the tuple has a lot of fields and is constructed far from where it is used. A namedtuple assigns names, as well as the numerical index, to each member. \n",
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"\n",
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"Each kind of namedtuple is represented by its own class, created by using the namedtuple() factory function. The arguments are the name of the new class and a string containing the names of the elements.\n",
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"\n",
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"You can basically think of namedtuples as a very quick way of creating a new object/class type with some attribute fields.\n",
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"For example:"
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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": 40,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"from collections import namedtuple"
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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": 47,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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"source": [
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"Dog = namedtuple('Dog','age breed name')\n",
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"\n",
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"sam = Dog(age=2,breed='Lab',name='Sammy')\n",
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"\n",
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"frank = Dog(age=2,breed='Shepard',name=\"Frankie\")"
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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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"We construct the namedtuple by first passing the object type name (Dog) and then passing a string with the variety of fields as a string with spaces between the field names. We can then call on the various attributes:"
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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": 42,
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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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"Dog(age=2, breed='Lab', name='Sammy')"
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]
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},
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"execution_count": 42,
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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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"sam"
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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": 43,
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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"
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]
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},
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"execution_count": 43,
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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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"sam.age"
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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": 44,
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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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"'Lab'"
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]
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},
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"execution_count": 44,
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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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"sam.breed"
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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": 45,
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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"
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]
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},
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"execution_count": 45,
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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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"sam[0]"
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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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"##Conclusion\n",
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"\n",
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"Hopefully you now see how incredibly useful the collections module is in Python and it should be your go-to module for a variety of common tasks!"
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]
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}
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],
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"metadata": {

‎.ipynb_checkpoints/Final Capstone Project-checkpoint.ipynb

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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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"collapsed": true
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},
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"source": [
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"#Final Capstone Projects\n",
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"\n",
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"Go to this link for the Descriptions and Code Outlines of several Capstone Projects!"
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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,

‎Advanced Functions Quiz.ipynb

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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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"#Advanced Functions Quiz"
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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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"collapsed": true
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},
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"outputs": [],
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"source": []
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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 2",
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"language": "python",
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"name": "python2"
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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": 2
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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": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}

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