CSAI2026 labs: Lab-2..Lab-6 (Practical + Solution, data), Module-2..Module-6 notebooks and datasets
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mikrotik
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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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"# Set and Booleans\n",
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"\n",
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"There are two other object types in Python that we should quickly cover: Sets and Booleans. \n",
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"\n",
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"## Sets\n",
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"\n",
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"Sets are an unordered collection of *unique* elements. We can construct them by using the set() function. Let's go ahead and make a set to see how it works"
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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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"tags": []
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},
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"outputs": [],
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"source": [
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"x = 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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"tags": []
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},
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"outputs": [],
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"source": [
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"# We add to sets with the add() method\n",
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"x.add(1)"
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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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"#Show\n",
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"x"
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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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"Note the curly brackets. This does not indicate a dictionary! Although you can draw analogies as a set being a dictionary with only keys.\n",
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"\n",
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"We know that a set has only unique entries. So what happens when we try to add something that is already in a 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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"tags": []
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},
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"outputs": [],
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"source": [
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"# Add a different element\n",
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"x.add(2)"
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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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"#Show\n",
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"x"
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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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"tags": []
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},
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"outputs": [],
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"source": [
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"# Try to add the same element\n",
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"x.add(1)"
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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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"#Show\n",
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"x"
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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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"Notice how it won't place another 1 there. That's because a set is only concerned with unique elements! We can cast a list with multiple repeat elements to a set to get the unique elements. 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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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"# Create a list with repeats\n",
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"list1 = [1,1,2,2,3,4,5,6,1,1]"
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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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"# Cast as set to get unique values\n",
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"set(list1)"
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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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"## Booleans\n",
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"\n",
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"Python comes with Booleans (with predefined True and False displays that are basically just the integers 1 and 0). It also has a placeholder object called None. Let's walk through a few quick examples of Booleans (we will dive deeper into them later in this course)."
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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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"tags": []
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},
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"outputs": [],
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"source": [
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"# Set object to be a boolean\n",
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"a = True"
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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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"#Show\n",
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"a"
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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 can also use comparison operators to create booleans. We will go over all the comparison operators later on in the course."
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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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"# Output is boolean\n",
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"1 > 2"
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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 can use None as a placeholder for an object that we don't want to reassign yet:"
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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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"tags": []
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},
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"outputs": [],
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"source": [
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"# None placeholder\n",
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"b = None"
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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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"# Show\n",
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"print(b)"
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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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"Thats it! You should now have a basic understanding of Python objects and data structure types. Next, go ahead and do the assessment test!"
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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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},
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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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}
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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": "3.8.8"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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