Data Types in Python | Python for Beginners
Summary
TLDRThis educational video script delves into Python's data types, essential for understanding how data is stored and manipulated. It covers numeric types like integers, floats, and complex numbers, explaining their characteristics and operations. The script progresses to Boolean values, emphasizing true or false states, and sequence types including strings, lists, and tuples, highlighting their indexing and mutability. It distinguishes between lists and tuples, noting the latter's immutability. Sets are introduced as unordered collections without duplicates, and their operations for unique value comparison are discussed. The script concludes with dictionaries, Python's key-value pair data structures, illustrating how they store and update data. The comprehensive overview is designed to solidify viewers' grasp of Python's foundational data types.
Takeaways
- 🔢 Data types in Python are essential for understanding how data is stored and manipulated, with numeric, sequence, set, Boolean, and dictionary types being the main categories.
- 📏 Numeric types include integers (whole numbers), floats (decimal numbers), and complex numbers (used for imaginary numbers).
- 🌟 Boolean type represents one of two values: True or False, and is often used in conditional statements and comparison operations.
- 📝 Sequence types consist of strings, lists, and tuples, with strings being arrays of bytes representing Unicode characters, and lists being ordered, mutable collections of items.
- 🍦 Tuples are similar to lists but are immutable, meaning they cannot be changed after creation, and are often used for data that should not change.
- 🔑 Sets are unordered collections of unique elements, without indices, and are useful for membership testing and eliminating duplicates.
- 📖 Dictionaries store data in key-value pairs, allowing for fast retrieval of values based on keys, and are mutable, allowing for updates and deletions.
- 🔍 Indexing in Python is used to access elements in data structures like strings and lists, starting from position 0, and can include negative indexing for reverse access.
- 🔄 Operations like addition, multiplication, and concatenation can be performed on strings and lists, but not on tuples due to their immutability.
- 🏷 Sets support operations like union, intersection, and difference, which are useful for comparing and manipulating collections of unique items.
- 🛠️ Dictionaries can be dynamically updated and elements can be added, modified, or removed using keys, providing a flexible way to handle data.
Q & A
What are the main data types in Python discussed in the script?
-The main data types in Python discussed are numeric, sequence, set, Boolean, and dictionary.
What are the three different types of numeric data types in Python?
-The three different types of numeric data types in Python are integers, floats, and complex numbers.
How can you verify the data type of a variable in Python?
-You can verify the data type of a variable in Python by using the 'type()' function, such as 'type(12)' to check if it's an integer.
What is the difference between an integer and a float in Python?
-An integer in Python is a whole number, positive or negative, without a decimal point. A float is a number with a decimal point, representing a fractional part.
What is a complex number in Python and how is it represented?
-A complex number in Python represents imaginary numbers and is represented by using 'j' as the imaginary unit, such as '12 + 3j'.
What are the two built-in values of the Boolean data type in Python?
-The two built-in values of the Boolean data type in Python are 'True' and 'False'.
How do you create a string in Python and what are the different ways to enclose it?
-You create a string in Python by enclosing characters in either single quotes (' '), double quotes (
What is the significance of indexing in Python strings and how does it work?
-Indexing in Python strings allows you to access specific characters or a range of characters within the string. It starts at 0, and you can use positive or negative indices to access characters from the beginning or end of the string.
How do lists differ from strings in Python, and what is a key feature of lists?
-Lists in Python differ from strings in that they can store multiple values, which can be of different data types. A key feature of lists is that they are mutable, meaning you can change, add, or remove items after creation.
What is a tuple in Python and how does it differ from a list?
-A tuple in Python is a collection of values, similar to a list, but it is immutable, meaning its values cannot be changed after creation. Tuples are defined using parentheses.
What is a set in Python and how does it differ from a list?
-A set in Python is an unordered collection of unique elements, which means it does not allow duplicate values. Unlike lists, sets do not support indexing and are defined using curly braces.
How can you compare two sets in Python to find common or unique elements?
-You can compare two sets in Python using set operations like union ('|'), intersection ('&'), difference ('-'), and symmetric difference ('^') to find common or unique elements between them.
What is a dictionary in Python and how is it different from other data types?
-A dictionary in Python is a collection of key-value pairs, where each key is unique. It is different from other data types in that it uses keys to access values, rather than using indices like in lists or tuples.
How do you access values in a dictionary in Python?
-In Python, you access values in a dictionary by using the keys, such as 'dictionary_name['key_name']'.
Can you update or delete values in a Python dictionary? If so, how?
-Yes, you can update values in a Python dictionary by assigning a new value to an existing key or by using the 'update()' method. You can delete values using the 'del' statement followed by the key or the 'pop()' method.
Outlines
🔢 Introduction to Python Data Types
This paragraph introduces the concept of data types in Python, explaining that they are classifications of data that determine the operations that can be performed on them. The video focuses on the main data types in Python, including numeric (integers, floats, and complex numbers), sequence types, sets, Boolean, and dictionaries. The speaker demonstrates how to check data types using the 'type()' function and provides examples of operations on integers, floats, and complex numbers, highlighting the differences between them.
📖 Exploring Python's Sequence Types and Strings
The speaker delves into sequence types, starting with strings. They explain that strings in Python are arrays of bytes representing Unicode characters and can be enclosed in single, double, or triple quotes. The paragraph covers string indexing, where the index starts at zero, and demonstrates how to access parts of a string using positive and negative indices. It also touches on string concatenation and repetition. The discussion then shifts to lists, which are mutable and can hold multiple values. Lists are indexed like strings, and the speaker shows how to create lists with both numeric and string values, including nested lists. The paragraph concludes with a demonstration of how lists can be modified after creation using methods like 'append' and how to change list items by index.
🍦 Tuples, Sets, and Their Unique Characteristics
This paragraph discusses tuples, which are similar to lists but are immutable, meaning they cannot be changed after creation. The speaker shows how to create a tuple and access its elements using indexing. Unlike lists, tuples do not support methods like 'append'. The paragraph then moves on to sets, which are unordered collections of unique elements and do not support indexing. The speaker demonstrates how to create a set and discusses the use of sets for comparing unique values between different collections. Various set operations like union, intersection, and difference are explained with examples.
📚 Diving into Python Dictionaries
The speaker introduces dictionaries, which are a collection of key-value pairs. Unlike lists and tuples, dictionaries are not indexed by integer indices but by keys. The paragraph explains how to create a dictionary and access its values using keys. It also covers methods to retrieve all keys, values, or items from a dictionary. The speaker demonstrates how to update dictionary values and entire key-value pairs using the 'update' method. The paragraph concludes with a discussion on deleting dictionary keys and their associated values using the 'del' statement.
👋 Wrapping Up the Data Types Discussion
In the final paragraph, the speaker summarizes the video's coverage of Python data types, expressing gratitude to the viewers for watching. They encourage viewers to like and subscribe for more content, hinting at future videos. The music plays as the video concludes, signaling the end of the data types discussion.
Mindmap
Keywords
💡Data Types
💡Integers
💡Float
💡Complex Numbers
💡Boolean
💡Sequence Types
💡Strings
💡Lists
💡Tuples
💡Sets
💡Dictionaries
Highlights
Introduction to data types in Python, which are classifications that determine what operations can be performed on data.
Explanation of numeric data types including integers, floats, and complex numbers.
Integers are whole numbers, positive or negative, demonstrated with examples.
Floats are non-whole numbers, introduced by performing an operation that results in a decimal.
Complex numbers are used for imaginary numbers and are denoted by 'J'.
Boolean data type with only two values: True or False, used in comparison operations.
Sequence type data includes strings, lists, and tuples, each with unique properties.
Strings are arrays of bytes representing Unicode characters, can be single, double, or triple quoted.
Demonstration of string indexing, showing how to access characters by position.
Lists store multiple values and are indexed, can contain different data types.
Lists are mutable, allowing items to be added, removed, or changed after creation.
Tuples are similar to lists but are immutable, meaning they cannot be changed once created.
Sets are collections without duplicate elements and do not support indexing.
Sets are unordered and can be used to find unique elements or differences between sets.
Dictionaries store key-value pairs and are used for more complex data associations.
Dictionaries allow for the updating and deletion of key-value pairs, but not direct indexing.
Overview of how to access and manipulate data within dictionaries using keys.
Conclusion of the data types video with a summary of the covered topics.
Transcripts
hello everybody today we're going to be
talking about data types in Python data
types are the classification of the data
that you are storing these
classifications tell you what operations
can be performed on your data we're
going to be looking at the main data
types within python including numeric
sequence type set Boolean and dictionary
so let's get started actually writing
some of this out and first let's look at
numeric there are three different types
of numeric data types we have integers
float and complex numbers let's take a
look at integers an integer is basically
just a whole number whether it's
positive or negative so an integer could
be a 12 and we can check that by saying
type
we'll do an open parentheses and a
closed parenthesis and if we say the
type of 12 it's going to give us an
integer or if we say a negative 12 that
is also an integer we can also perform
basic calculations like -12 plus 100 and
that'll tell us it is also an integer so
whether it's just a static value or
you're performing an operation on it
it's still going to be that data type if
those numbers are whole numbers whether
negative or positive now let's take this
exact one and let's say 12 and we'll do
plus
10.25 when we run this it's no longer
going to be a whole number it'll now be
a float so let's check this and now this
is a float type because it's no longer a
whole number it's now a decimal number
and the last data type within the
numeric data type is called complex
let's copy this right down here now
personally this is not one that I've
used almost ever but it is one just
worth noting so you can do 12 plus and
let's say 3 J and if we do this is going
to give us a complex the complex data
type is used for imaginary numbers for
me it's not often used but if you do use
it J is used as that imaginary number if
you use something like C or any other
number it's going to give you an error J
is the only one that will work with it
now let's take a look at Boolean values
so we'll say Boolean the Boolean data
type only has two built-in values either
true or false so let's go right down
here and say type true
and when we run this it'll say Bool
which stands for Boolean we can do the
exact same thing with false and that is
also Boolean and this can be used with
something like a comparison operator so
let's say one is greater than 5. and
let's check this this is giving us a
Boolean because it's telling us whether
one is greater than 5. let's bring that
right down here this will give us a
false so it's telling us that one is not
greater than 5. and just as we got a
false we can say 1 is equal to one and
this should give us a true so now let's
take a look at our sequence type data
types and that includes strings lists
and tuples we'll start off by looking at
strings
in Python strings are arrays of bytes
representing Unicode characters when
you're using strings you put them either
in a single quote a double quote or a
triple quote I call them apostrophes
it's just what I was raised to call them
but most people who use Python call them
quotes So Right Here we have a single
quote
and that works well we can do a double
quote
and that works also and as you can see
they are the exact same output and then
we have a triple quote just like this
and this is called a multi-line so we
can write on multiple lines here so
let's write a nice little poem so we'll
say the ice cream
vanquished my longing for sweets
upon this diet
I look away
it no longer exists
on this day
and then if we run that it's going to
look a little bit weird it's basically
giving us the raw text which is
completely fine but let's call this a
multi-line
we're going to call this a variable
multi-line and we're going to come down
here and say print
and before I run this I have to make
sure that this is ran
so now let's print out our multi-line
and now we have our nice little poem
right down here now something to know
about these single and double quotes is
how they're actually used so if we use a
single quote and we say I've always
wanted to eat a gallon of ice cream
and then we do an apostrophe at the end
obviously something went wrong here what
went wrong is when you use a single
quote and then within your text within
your sentence you have another
apostrophe it's going to give you an
error so what we want to do is whenever
we have a quote within it we need to use
a double quote these double quotes will
negate any single quotes that you have
within your statement they won't however
negate another double quote so you need
to make sure you aren't using double
quotes within your sentence if you want
to do something like that you need to
use the triple quotes like we did above
so we can do double double
and then let's paste this within it
and anything you do Within These treble
quotes will be completely fine as long
as you don't do triple quotes within
your triple quotes we'll say this is
wrong so even though it's between these
two triple quotes it doesn't work
exactly again you just have to
understand how that works you have to
use the proper apostrophes or quotes
within your string and just to check
this we can always say here's our
multi-line we can always say type
of multi-line and that is still a string
one really important thing to know about
strings is that they can be indexed
indexing means that you can search
within it and that index starts at zero
so let's go ahead and create a variable
and we'll just say a is equal to and
let's do the all popular
hello world let's run this
and now when we print the string we can
say a and we're going to do a bracket
and now we can search throughout our
string using the index so all you have
to do is do a colon we can say five what
this is going to do is going to say 0
position 0 all the way up to five which
should give us the whole hello I believe
let's run this and it's giving us the
first five positions of this string we
can also get rid of the colon and just
say something like five
and then when we run this it's actually
going to give us position five so this
is 0 1 2 3 4 and then 5 is the space
let's do six so we can see the actual
letter and that is our w we can also use
a negative when we're indexing through
our string so we could say negative
three and it'll give us the L because
it's negative one two and three we can
also specify a range if we don't want to
use the default of zero so before we did
zero to five and it started at zero
because that was our default but we
could also do two to five let's run this
and now we go position 0 1 and then we
start at 2 L L O now we can also
multiply strings and we have this a
hello world so we can do a
times three and if we run this it'll
give us hello world three times and we
can also do a plus a
and that is Hello World hello world now
let's go down here and take a look at
lists lists are really fantastic because
they store multiple values the string
was stored as one value multiple
characters but a list can store multiple
separate values so let's create our very
first list we'll say list really quickly
and then we'll put a bracket and a
bracket means this is going to be a list
there are other ones like a squiggly
bracket and a parenthesis these denote
that they are different types of data
types the bracket is what makes a list a
list so to keep it super simple we'll
say one two three and we'll run this and
now we have a list that has three
separate values in it the comma in our
list denotes that they are separate
values and a list is indexed just like a
string is indexed so position zero is
this one position one is the two and
position two is the three now when we
made this list we didn't have to use any
quotes because these are numbers but if
we wanted to create a list and we wanted
to add string values we have to do it
with our quotes so we'll say quote
cookie dough
then we'll do a comma to separate the
value and then we'll say
strawberry
then we'll do one more and this will
just be chocolate and when we run this
we have all three of these values stored
in our list now one of the best things
about lists is you can have any data
type within them they don't just have to
be numbers or strings you can basically
put anything you want in there so let's
create a new list
and let's say vanilla
and then we'll do three and then we'll
add a list within a list and we'll say
scoops
comma spoon and then we'll get out of
that list and then we'll add another
value of true for Boolean and now we can
hit shift enter and we just created a
list with several different data types
within one list
now let's take this one list right here
with all of our different ice cream
flavors we'll say ice underscore cream
is equal to this list now one thing
that's really great about lists is that
they are changeable that means we can
change the data in here we can also add
and remove items from the list after
we've already created it so let's go and
take ice cream and we'll say ice cream
dot append and this is going to append
it to the very end of the list we'll do
an open parenthesis let's say salted
caramel now when we run this and we call
it just like this it's going to take
this list add salted caramel to the end
and we'll print it off and as you can
see it was added to the list and just
like I said before let me go down here
we can also change things from this list
so let's say ice cream and then we need
to look at the indexed position so we're
going to say 0 and that's going to be
this cookie dough right here we can say
that is equal to so we can now change
that value so let's call that butter
econ
and now when we call it
we can now see that the cookie dough was
changed to butter pecan another thing
that you saw just a little bit ago is
something called a list within a list
basically a nested list so we had Scoops
spoon true let's give this and we'll say
nested underscore list is equal to
now when we run this we now have this
nested list so if we look at the index
and we say 0 we'll get vanilla if we say
2 we'll get scoops and spoons now since
we have a list within a list we can also
look at the index of that nested list so
let's now say one and that should give
us just spoon and you can go on and on
and on with this you can do lists within
lists within lists and all of them will
have indexing that you can call now
let's go down here and start taking a
look at tuples so we list in a tubal are
actually quite similar but the biggest
difference between a listen a tuple is
that a tuple is something called
immutable it means it cannot be modified
or changed after it's created let's go
right up here we're going to say
tubal
and let's write our very first Tuple so
we'll say Tuple underscore scoops
is equal to and then we'll do an open
parenthesis now these open parentheses
you've seen if you do like a print
statement but that's different because
that's executing a function this is
actually creating a tuple which is going
to store data for us so we'll say one
two three
two and one let's go ahead and create
that Tuple and we can just check the
data type really quickly
and it's a tuple and just like we saw
before a tuple is also indexed so if we
go at the very first position which is a
one we will get the output of a one but
we can't do something like append
and then add a value like three if we do
that it's going to say Tuple object has
no attribute append it's just because
you cannot change or add anything to a
tuple just like we were talking about
before typically people will use tuples
for when data is never going to change
an example for this might be something
like a city name a country a location
something that won't change they
definitely have their use cases but I
don't think they're as popular as just
using a list so now let's scroll down
and start taking a look at sets but
really quickly let me add a few more
cells for us
and let's say sets
now a set is somewhat similar to a list
in a tuple but they are a little bit
different in fact that they don't have
any duplicate elements another big
difference is that the values within a
set cannot be accessed using an index
because it doesn't have an index because
it's actually unordered we can still
Loop through the items in a set with
something like a for Loop but we can't
access it using the bracket and then
accessing its index point so let's go
ahead and create our very first set so
we're going to say daily underscore
pints then we're going to say equal to
and to create a set we're going to use
these squiggly brackets I don't know if
there's an actual name for those if I'm
being honest I call them squiggly
brackets and that's what we're going to
go with we're going to put in a one a
two and a three so let's go ahead and
run this
and let's look at the type
and as you can see it is a set now when
we print this out
it's going to show us one a two and a
three and those are all the values
within our set but if we copy this and
we'll say daily pints log this is going
to be every single day
maybe I had different values
now when we run this and we do the exact
same thing now when we print this
it's going to have just the unique
values within that set now a use case
for set and this is something that I've
done in the past is comparing two
separate sets maybe you have a list or a
tuple and you convert that into a set
and that will narrow it down to its
unique values and then you can compare
the unique values of one set to the
unique values in another set and then we
can see what's the same and what's
different so let's go down here and
let's say wife's underscore daily and
we'll just copy this right here we'll
say is equal to let's do our squiggly
lines let's do one two let's do just
random numbers
so now this is my daily log and this is
my wife's daily log and now we can
compare these values so let's go right
down here let's say print
we'll do my daily logs and then we'll do
this bar right here and this is going to
show us the combined unique values it's
basically like putting them all in one
set and then trimming it down to just
the unique values so we'll take wife's
daily pints log
and when we run this we actually need to
run this first
when we run this we should see all the
unique values between these two sets and
so as you can see zero one two three
four five six seven twenty four Thirty
One so these are all the unique values
between these two sets
we can also do another one
and instead of this bar we're gonna do
this symbol right here which I believe
is called an ampersand don't quote me on
that but when we run this it's going to
show what matches that means which ones
show up in both sets so the only ones
that show up in both sets are one two
three and five we can also do the
opposite of that by doing a minus sign
and this is going to show us what
doesn't match so we have 4 6 and 31. now
where is our 24 that was in our wife's
daily pints log it's in this one but
we're subtracting the values on this one
so let's reverse this and we'll say
daily pints log
and let's run it now those are our other
values so we're taking the values of
this and then we're subtracting all the
ones that are the same and getting the
remaining values and then for our last
one
we can get rid of this and we'll do this
symbol right here and this is going to
show if a value is either in one or the
other but not in both so let's run this
so these values are completely unique
only to each of those sets now the very
last one that we're going to look at in
this video is dictionaries so let's go
right down here
let's add a few cells and let's say
dictionaries
now I saved dictionary for last because
this one is probably the most different
out of all the previous data types that
we've looked at within a data type we
have something called
a key
value pair
that means when we use a dictionary it's
not like a list where you just have a
value comma value comma value we have a
key that indicates what that value is
attributed to so let's write out a
dictionary to see how this looks we're
going to say dictionary underscore cream
and just like a set we use a squiggly
line but the thing that differentiates
it is that in a dictionary we'll have
that key value pair whereas in a set
each value is just separated by a comma
so let's write name
and this is our key and then we do a
colon and this is then where we input
our value so we're going to say Alex
freeberg
and then we separate that key value Pair
by a comma and now we can do another key
value pair so we'll say
weekly intake
and a colon and we'll say five pints of
ice cream do a comma and then we'll do
favorite ice creams
and now what we're going to do is we're
going to put in here a list so within
this dictionary we can also add a list
we'll do MCC for mint chocolate chip and
then we'll add chocolate another one of
my favorites so now we have our very
first dictionary let's copy this and run
it
and let's just look at the type
and as you can see it says that this is
a dictionary let's also print it out
now if we want to we can take our
dictionary cream and say dot values with
an open parenthesis when we execute this
we'll see all of the values within this
dictionary so here's our values of Alex
freeberg five mint chocolate chip and
chocolate
we can also say keys
and when we run this all of the keys the
name weekly intake and favorite ice
creams
and we can also say
items so this key value pair is one item
and this key value pair is another item
now one difference between something
like a list and a dictionary is how you
call the index but you can't call it by
doing something like this where you just
do a bracket oops and say zero so this
would in theory take this very first one
right our very first key value pair
that's going to give us an error how you
call a dictionary is actually by the key
so it doesn't technically have an index
but you can specify what you want to
call and take it out so we're going to
say name and this is going to call that
key right here and when we run this
we'll get the value which is Alex
freeberg one other thing that you can do
is you can also update information in a
dictionary which we can't with some
other data types so for this for the
name it was Alex freeberg now let's say
Steen freeberg
and when we update that I'm also going
to print
the dictionary get rid of this so it's
going to update Christine freeberg in
that value of the name so let's go ahead
and run this
and now it changed the name from Alex
freeberg to Christine freberg we can
also update all of these values at one
time so let's copy this
and I'm going to put it right down here
I'm going to say dictionary.cream dot
update then we're going to put a bracket
or not a bracket but a parentheses
around these so now what we're going to
do is update this entire thing let me
take this
say print this dictionary now we can
update this to anything we want so
instead of here I can say
I'll say wait
and because of all that ice cream I now
weigh 300 pounds so let's run this
and as you can see it did not delete our
key value pair right here instead of
just added to it when you're using the
update we can't actually delete that's
the delete statement and I'll show you
that in just a second but all we did was
added this new value it also is going to
check and see if you changed anything
with your key value pair so we can go in
here and change this value and we'll say
10. so now when we run this the value of
this key value pair was changed but
let's say we do want to delete it we'll
say Del that stands for delete
part of this dictionary cream and now
let's specify the key which will also
delete the value with it let's specify
the key that we want to get rid of and
let's say wait
and then let's print that again
and as you can see the weight was
deleted from that dictionary so that is
all we're going to cover in this data
types video thank you guys so much for
watching I really appreciate it if you
like this video be sure to like And
subscribe below and I'll see you in the
next video
[Music]
foreign
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