1. Introduction to Python
2. Python Basics (syntax, variables, data types)
3. Python Operators
4. Python If…Else
5. Python While Loops
6. Python For Loops
7. Python Functions
8. Python Lambda
9. Python Arrays
10. Python Classes and Objects

welcome to python proigramming. here we shall look at how to get strated with python programming. we shall begin from thee basics and navigate all the way up. our main goal is to create a django project using the django gframework

Python identation: Here we shall talk about the python syntax, in python we don’t use the semicolon to show the end of a statement, instead wqe use what we call python identation. We shall look at an example below.

the above are some of the common examples that use python identation. THE EXAMPLES ABOVE COVER A WHILE LOOP WITH SOME conditiuons(pass, break anmd continue) these are added so that the while loop is altered in the way it runs the code.

The above code also illustraytes the impact of python identation but now this case is of using the if statement

The above code shows comments in python. comments are usefulas they hjelp the programmers understand each others code. They also work as reminder notes that is if some

Inthe above example you notice the one with a preceeding hash is not printed out as it is read as a comment

In the above cell you notice that the sentence with the three quotation marks is not printed out as it is read as a comment

The above describes how you can create varibles and also show their oputput. In the above example that is how we create variables. In the cells below we shall discuss how we create casting of vaiables, this is used to convert a given datatype of form ‘A’ to form ‘B’

Note when assinging variables to strings you can either use single or double Quotes

The above example tries to emphasize on the importance of case sensitivity in python programming

the above code illustrates a good way of how you can assign a single bvalue to multiple variables

In the above code we see how a collection which uses the list data type can be unpacked. this is done by assigning the variables to the list

the above code is used to show how the python outputs it’s variables. variables can be outputed using print() function

The above code is used to print the output of x and y which will print the sum note if you tried to add the sum of an integer and a string it would not work

The above cell shows how the output of many variables can be printed out

from the above example we have made y the global variable that is considering that y is also in the fuinction above myfunc(), the making og global variable has occured by using the global keyword

In the above code we can see that both x and y are global variables and are being used by the 2 functions area() and perimeter()

The above pioece of code shows the examples of different data types in python. the datatypes in python are very crusial as they are the building block of pytrhon programming and must be understood very well for one to have a mastery in python.

also note they can be negatives also below is an example to illustrate that

we shall discuss about type conversion in the subsequent cells, sometimes you will need to convert a certain data type from one Form to another then use the converted datatype

In the above code we see that the type casting has been used

below is an example of the random numbers

The above statements or code show how youcan use the random to generate number data type

The above lines of code show how one can implement the use of strings in python. Note that hello world is a string.

So what is a string in python? A string in python is surrounded by quotation marks ether single quotation mark or Double Quotation mark

# Strings in Python

Introduction

In Python, a string is a sequence of characters enclosed in single quotes (”), double quotes (” “), or triple quotes (”’ ”’ or “”” “””). Strings are immutable, meaning they cannot be changed after they are created.

Creating Strings

Strings can be created using single quotes, double quotes, or triple quotes:

“`python

Single quotes

single_quoted_string = ‘Hello, World!’

Double quotes

double_quoted_string = “Hello, World!”

Triple quotes (for multi-line strings)

triple_quoted_string = ”’Hello, World!”’

Strings in python are surrounded by a single quote orv a double quote. The strings are also written in different formats.

Slicing of strings

From the data above we shall use the KMeans algorithim

Machine learning using scikitlearn module

Loading an example dataset

Slice From the Start

the above piece of code explains the string slicing from index 2 to index 5 only that now index 5 is not inclusive here is how the slicing works hello-0 for h, 1-e,2-l,3-l,4-o so we can see that indexing starts from zero then progresses as we continue. In the cells below we shal;l also have negative indexing.

note you can’t use -2:-4 as -2 is greator than -$ so the order is as this , so lets see why we have the output. so we go to -4 counting from the right and end at o and then go to -2 counting from the right and end up at l which is not inclusive, the special case is that we are starting out count from -1 not 0 as in the normal case. We shall look at at a more interesting case that use the step in the cell below.

In the above code we can see an additional 2 at the end which indicated the step size or the gap between the elements we want to get. Here we note that the gap is of 2 units that means from -8 we write it down and jump 2 steps to get -6 then write it down then to -4 and finally to -2 which is not inclusive. at -8 we find that we have l and at -6 we find that we have a gap and at -4 we have an o that is why we have the output above with a gap between l and o.

Python – Modify Strings

Explaining the output above wqe find that the .upper() method converts our string into an upper case also we find that the .lower() function converts the string into a lower case, finally we can see that the .strip gets rid of the spaces that were preceeding the string. These are the common types of python string modifications. We also see the .replace have replaced the H with ch this is also another modification that can be done to strings. The split method also splits the string into 2 words returning a list of the string content the contents take the list data structure.

Python – String Concatenation

in the above example we can witness concatenation ast the strings x and y are joined together using the + sign and also we can see that adding an empty space betwen them can be obtained by having a space betweenm the quotation marks

Python – Format – Strings

The above code shows how we can achieve formatting as one of the ways we can use an f and also this is helpful as we can see that the we can use integers and strings together this means we can now not get worried about the data type we are using. Note in the socond print we have used the format method which is also an alternative this makes use also of the empty carry bracket.

Python – Escape Characters

Escape Character To insert characters that are illegal in a string, use an escape character.

An escape character is a backslash  followed by the character you want to insert.

In the above we note that the apostrophe is at the end of the s where we note another  backslash that tells our computer what that is.

In the above the x shall be the one we are experimentinmg with and we see that we shall have a new line where the next line after \n will be printed note python is intelligent enough to know that the \n is an escape character and that it means print in a new line.

Python Booleans

The above is a boolean argument that shows True when the value 12 is greator than 10 if 10 was less than 12 it would show False ie print(10>12)

Evaluate Values and Variables

Most Values are True

Some Values are False

Functions can Return a Boolean

The above piece of code shows a function myfunction() and it returns True as the otput which is a boolean Data Type

This is the code that shows if the condition is set and prints out if False once the condition of the function is False otherwise True if the condition is True

Check if an object is an integer or not:

The above returns True if the X value is an integer and False if X is not an integer In this case the X was being tested with the str to show if it is a string. that is in the second part.

Python Operators

Python divides the operators in the following groups:

1. Arithmetic operators
2. Assignment operators
3. Comparison operators
4. Logical operators
5. Identity operators
6. Membership operators
7. Bitwise operators

Python Arithmetic Operators

Python Assignment Operators

Python Comparison Operators

Python Logical Operators

Python Identity Operators Identity operators are used to compare the objects, not if they are equal, but if they are actually the same object, with the same memory location:

is Returns True if both variables are the same object x is y

is not Returns True if both variables are not the same object x is not y

Let’s break down the code:

x=[1,2,3,4,5,6,7,8,9]: This creates a list x containing the numbers 1 to 9.

y=x: This assigns the list x to the variable y. Now, y also refers to the same list as x.

print(2 in x): This checks if the value 2 is present in the list x. Since 2 is in the list, this will print True.

print(122 not in x): This checks if the value 122 is not present in the list x. Since 122 is not in the list, this will print True.

print(x is [1,2,3,4,5,6,7,8,9]): This checks if the variable x is exactly the same object as the list [1,2,3,4,5,6,7,8,9]. However, even though the contents of x and [1,2,3,4,5,6,7,8,9] are the same, they are not the same object in memory. So, this will print False.

Python Membership Operators Membership operators are used to test if a sequence is presented in an object

in Returns True if a sequence with the specified value is present in the object x in y

not in Returns True if a sequence with the specified value is not present in the object x not in y

Python Lists List Lists are used to store multiple items in a single variable.

Lists are one of 4 built-in data types in Python used to store collections of data, the other 3 are Tuple, Set, and Dictionary, all with different qualities and usage.

Lists are created using square brackets:

In the above three code : We see that the list bdata structure in python can be created in different ways the secxond parts shows creating the lists using the list constructor, on the other hand you can create a list data structure using the square carry brackets or use the list constructor.

List Items

List items in Python lists are ordered, changeable, and allow duplicate values.

Ordered

Lists maintain the order in which items are added. When new items are added, they are placed at the end of the list. While there are methods that can change the order, the general rule is that the order remains the same.

Changeable

Lists are mutable, meaning you can change, add, and remove items from a list after it has been created.

Allow Duplicates

Lists can contain duplicate values. Since lists are indexed, items with the same value can exist in the list.

Example: Lists allow duplicate values:

“`python my_list = [1, 2, 3, 3, 4, 5] print(my_list)

IN THE ABOVE CODE WE CAN SEE THAT

Apple is dublicated thus creating a dublicate.

in the above code we see that the number 66 is repeated twice and python list allows that but in python sets that is not allowed

Analysing the code above we see that the index of number 33 is 2 and thus to get the elements we start counting from 0 and progress.

In the above code we see that the index is iterated using the for loop and we can get the index for all the list items thus we see that the index are counted from 0and this is matched to the first element in the list. The enumerate function returns tuples (index, value) for each element in the list

Access Items in a list

The above code can be what we say is slicing of lists or getting a range of the list data in the cell below we shall remind ourselves about slicing of strings.

Checking if an item is in the list bold text

in the above code we iterate the list and we find that we iterate through the list and we find that a for loop does it well.

Check if Item Exists

in the above code we see that we can check if the elements in a list are present or not and also we can check if they are there in the list.

Python – Change List Items

From the above we note that we can change list items after identifying their position using idexing, in this case we can see that item in index 5 is 6 and thus this is changed to the value 1223

in the above piece of code we can see that the range is given from the index 2 to index 5 now our main focus is to first identify index 2 then traverse to index 5 note that the index 5 is not inclusive of the change as the range only affects the first 4 elements.

Insert Items To insert a new list item, without replacing any of the existing values, we can use the insert() method.

The insert() method inserts an item at the specified index:

This will insert the elements [223, 3, 99] at index 1 in the list j. j[1:1] refers to a slice of the list j starting at index 1 and ending just before index 1, which effectively selects an empty slice at index 1. After this operation, the list j will contain [1, 223, 3, 99, 2, 3, 4, 5, 6, 7, 8, 9], with the elements [223, 3, 99] inserted at index 1.

Python – Add List Items

If you tried to assign a variable to the d.append you would get none as the retuned value this is because append does not return any value, also note that append only takes one argument and giving many arguments to append you will enconter an error thus we have given one argument that is value 100

Insert Items To insert a list item at a specified index, use the insert() method.

The insert() method inserts an item at the specified index:

The above piece of code i used to insert the given value 266566 into the position of index 1 in the list, the item in index 1 is 2 and this is where the value is going to be inserted.

Extend List To append elements from another list to the current list, use the extend() method.

In the above piece of code we find that the extending operation has taken place and we see that the list w has been concatenated to list z this is what we call extrending of python lists, it is useful as they help in modifying the list data type

From the above example we can always extend the list with other iteratable datastructures this is what we have implemented in the above example.

bold textPython – Remove List Items

in the above piece of code we can see that the .remove function is being bused to remove the element 1 from our list, using the .remove() we can get rid of item we don’t need in our list the above example is a good example to explain that.

Note in the .remove() we don’t need to give the index of the item to remove we just list it and get rid of it right away that is the beauty of.remove()

What if we want to delete the list completly we can use the keyword del in the example below we shall see how del can be used to delete a list completly

Clear the List The clear() method empties the list.

The list still remains, but it has no content.

Python – Loop Lists Loop Through a List You can loop through the list items by using a for loop:

Python – List Comprehension List Comprehension List comprehension offers a shorter syntax when you want to create a new list based on the values of an existing list.

Example:

Based on a list of fruits, you want a new list, containing only the fruits with the letter “a” in the name.

Without list comprehension you will have to write a for statement with a conditional test inside:

Example

The Syntax newlist = [expression for item in iterable if condition == True]

The return value is a new list, leaving the old list unchanged.

Condition The condition is like a filter that only accepts the items that valuate to True.

Example Only accept items that are not “apple”:

The condition if x != “apple” will return True for all elements other than “apple”, making the new list contain all fruits except “apple”.

The condition is optional and can be omitted:

Example With no if statement:

Iterable The iterable can be any iterable object, like a list, tuple, set etc.

Example You can use the range() function to create an iterable:

Same example, but with a condition:

Example Accept only numbers lower than 5:

Expression The expression is the current item in the iteration, but it is also the outcome, which you can manipulate before it ends up like a list item in the new list:

Example Set the values in the new list to upper case:

You can set the outcome to whatever you like:

Example Set all values in the new list to ‘hello’:

The expression can also contain conditions, not like a filter, but as a way to manipulate the outcome:

Example Return “orange” instead of “banana”:

Python – Sort Lists

Sort List Alphanumerically List objects have a sort() method that will sort the list alphanumerically, ascending, by default:

Example

Sort the list alphabetically:

Sort Descending To sort descending, use the keyword argument reverse = True:

Example Sort the list descending:

Python – Copy Lists Copy a List You cannot copy a list simply by typing list2 = list1, because: list2 will only be a reference to list1, and changes made in list1 will automatically also be made in list2.

There are ways to make a copy, one way is to use the built-in List method copy().

Example

Python – Join Lists Join Two Lists There are several ways to join, or concatenate, two or more lists in Python.

One of the easiest ways are by using the + operator.

Example

Another way to join two lists is by appending all the items from list2 into list1, one by one:

Example Append list2 into list1:

Tuple Length

To determine how many items a tuple has, use the len() function:

Create Tuple With One Item To create a tuple with only one item, you have to add a comma after the item, why otherwise Python will not recognize it as a tuple.

Tuple Items – Data Types Tuple items can be of any data type:

A tuple can contain different data types:

Example

A tuple with strings, integers and boolean values:

tuple1 = (“abc”, 34, True, 40, “male”)

type() From Python’s perspective, tuples are defined as objects with the data type ‘tuple’:

Example What is the data type of a tuple?

mytuple = (“apple”, “banana”, “cherry”) print(type(mytuple))

The tuple() Constructor It is also possible to use the tuple() constructor to make a tuple.

Python – Access Tuple

Items Access Tuple Items You can access tuple items by referring to the index number, inside square brackets:

Negative Indexing in Python

Negative indexing is a feature in Python that allows you to access elements from the end of a sequence, such as a list or a tuple. When you use negative indices, Python starts counting from the end of the sequence, with -1 referring to the last item, -2 referring to the second last item, and so on.

Example:

Consider a list my_list = [10, 20, 30, 40, 50]. Using negative indexing, you can access elements as follows:

• my_list[-1] would return 50, which is the last item in the list.
• my_list[-2] would return 40, the second last item.
• my_list[-3] would return 30, the third last item.
• And so on…

Usage:

Negative indexing can be useful when you need to access elements from the end of a sequence without knowing its length. It provides a convenient way to access items from the end of a list or tuple without having to calculate the index manually.

Note:

• Negative indexing works with strings, lists, tuples, and other sequence types in Python.
• When using negative indices, remember that -1 refers to the last item, -2 refers to the second last item, and so on.

Range of Indexes in Python

You can specify a range of indexes in Python to extract a portion of a sequence, such as a list or tuple. The syntax for specifying a range is [start:end], where start is the index to start from (inclusive) and end is the index to end at (exclusive).

Example:

Consider a tuple thistuple = ("apple", "banana", "cherry", "orange", "kiwi", "melon", "mango"). To extract the third, fourth, and fifth items, you would use the range [2:5] as follows:

“`python thistuple = (“apple”, “banana”, “cherry”, “orange”, “kiwi”, “melon”, “mango”) print(thistuple[2:5])

Python – Update Tuples

Tuples are unchangeable, meaning that you cannot change, add, or remove items once the tuple is created.

But there are some workarounds.

Change Tuple Values Once a tuple is created, you cannot change its values. Tuples are unchangeable, or immutable as it also is called.

But there is a workaround. You can convert the tuple into a list, change the list, and convert the list back into a tuple.

Add Items

Since tuples are immutable, they do not have a built-in append() method, but there are other ways to add items to a tuple.

1. Convert into a list: Just like the workaround for changing a tuple, you can convert it into a list, add your item(s), and convert it back into a tuple

1. Add tuple to a tuple. You are allowed to add tuples to tuples, so if you want to add one item, (or many), create a new tuple with the item(s), and add it to the existing tuple:

Example Create a new tuple with the value “orange”, and add that tuple:

Remove Items Note: You cannot remove items in a tuple.

Tuples are unchangeable, so you cannot remove items from it, but you can use the same workaround as we used for changing and adding tuple items:

Or you can delete the tuple completely:

Python – Unpack Tuples Unpacking a Tuple When we create a tuple, we normally assign values to it. This is called “packing” a tuple:

The above asteriks shows that the unpacking of tuples will happen and the rest of items that have astericks take the remaining items in the fruits truple

Python – Loop Tuples Loop Through a Tuple You can loop through the tuple items by using a for loop.

Loop Through the Index Numbers You can also loop through the tuple items by referring to their index number.

Use the range() and len() functions to create a suitable iterable.

Iterating Over a Tuple in Python

Consider the following code snippet:

“`python thistuple = (“apple”, “banana”, “cherry”)

for i in range(len(thistuple)): print(thistuple[i])

Iterating Over a Tuple in Python

This code snippet demonstrates how to iterate over a tuple in Python using a for loop and range.

Creating a Tuple:

• thistuple = ("apple", "banana", "cherry"): This line creates a tuple named thistuple with three elements: “apple”, “banana”, and “cherry”.

For Loop with Range:

• for i in range(len(thistuple)):: This line sets up a for loop that iterates over the indices of thistuple.
• len(thistuple) returns the length of the tuple, which is 3 in this case.
• range(len(thistuple)) generates a sequence of numbers from 0 to 2 (length-1), which corresponds to the indices of the tuple.

Accessing and Printing Elements:

• Inside the for loop, thistuple[i] accesses the element of thistuple at index i and prints it.
• So, during the first iteration, thistuple[0] prints “apple”, during the second iteration, thistuple[1] prints “banana”, and during the third iteration, thistuple[2] prints “cherry”.

Usage:

• This approach allows you to iterate over each element in a tuple and perform operations on them.
• It is especially useful when you need to access both the index and the value of each element in the tuple.

Note:

• Python’s range() function generates a sequence of numbers that can be used to iterate over a sequence (like a tuple, list, or string) using indices.
• Using range(len(thistuple)) is a common pattern for iterating over the indices of a tuple or list to access each element.

Python – Join Tuples Join Two Tuples To join two or more tuples you can use the + operator:

Multiply Tuples If you want to multiply the content of a tuple a given number of times, you can use the * operator:

Python – Tuple Methods Tuple Methods Python has two built-in methods that you can use on tuples.

count() Returns the number of times a specified value occurs in a tuple

index() Searches the tuple for a specified value and returns the position of where it was found

Python Sets

From the above code we can see that there are 2 ways to create sets, the first is using carry brackets like in mathematics and the second is using the set constructor like in the second case.

Set Items in Python

In Python, a set is a collection data type that is unordered, unchangeable, and does not allow duplicate values.

Unordered:

• Sets are unordered, meaning that the items in a set do not have a defined order.
• Unlike sequences such as lists or tuples, you cannot access set items by index or key.
• Each time you use a set, its items may appear in a different order.

Unchangeable:

• Set items are unchangeable, or immutable. Once a set is created, you cannot change its items.
• This means you cannot change, replace, or modify individual items in a set.
• However, you can add new items to a set or remove existing items from it.

Duplicates Not Allowed:

• Sets do not allow duplicate values. If you try to add an item that is already in the set, it will not be added again.
• This property makes sets useful for tasks where you need to store a collection of unique items.

Example:

“`python my_set = {“apple”, “banana”, “cherry”}

We note that the dublicates were not included in our output as they appeared in the set

From the above piece of code we see that the False and True are also treated as same as 1,0

Set Items – Data Types Set items can be of any data type:

Python – Access Set Items

Access Items You cannot access items in a set by referring to an index or a key.

But you can loop through the set items using a for loop, or ask if a specified value is present in a set, by using the in keyword.

The above shows a list of the set items that are listed after being subjected to the for loop.

Here we see that only the items in the set are listed in a plain way.

Change Items

Once a set is created, you cannot change its items, but you can add new items.

From the above we see that the set has become longer after the update operation on the set s, so by using update we can make the set longer

Add Any Iterable The object in the update() method does not have to be a set, it can be any iterable object (tuples, lists, dictionaries etc.).

Python – Remove Set Items Remove Item To remove an item in a set, use the remove(), or the discard() method.

Note: If the item to remove does not exist, remove() will raise an error.

Note: If the item to remove does not exist, discard() will NOT raise an error.

You can also use the pop() method to remove an item, but this method will remove a random item, so you cannot be sure what item that gets removed.

The return value of the pop() method is the removed item.

Remove a random item by using the pop() method:

Note: Sets are unordered, so when using the pop() method, you do not know which item that gets removed.

Python – Loop Sets Loop Items You can loop through the set items by using a for loop:

You can use the | operator instead of the union() method, and you will get the same result.

Join Multiple Sets

All the joining methods and operators can be used to join multiple sets.

When using a method, just add more sets in the parentheses, separated by commas:

Join a Set and a Tuple

The union() method allows you to join a set with other data types, like lists or tuples.

The result will be a set.

In the above code we have created the union of set x with tuple y

Note that union() is only availlable in the set but not availlable in the list and tuple thus we must use the y.union() and not x.union() or z.union()

Note: The | operator only allows you to join sets with sets, and not with other data types like you can with the union() method.

Update

The update() method inserts all items from one set into another.

The update() changes the original set, and does not return a new set.

Note: Both union() and update() will exclude any duplicate items.

Intersection

Keep ONLY the duplicates

The intersection() method will return a new set, that only contains the items that are present in both sets.

In the above we see trhat intersection of sets is the common items in set a and set b that is what we call the intersection of a set

We can also use the & operator instead of the intersection()

in the above examples we see that the set3 can also be achieved by using the ampersurd sign

Note: The & operator only allows you to join sets with sets, and not with other data types like you can with the intersecton() method.

The intersection_update() method will also keep ONLY the duplicates, but it will change the original set instead of returning a new set.

In the above piece of code we see that the list of all common items in the set set1 and list list1 and tuple tuple1 are all listed in after the intersection. Note that the intersection is always used with the set.

This code snippet demonstrates the use of the intersection_update method in Python sets.

set1 contains the elements {“apple”, “banana”, “cherry”}.

set2 contains the elements {“google”, “microsoft”, “apple”}.

The intersection_update method modifies set1 to contain only the elements that are common between set1 and set2.

After the operation, set1 will be {“apple”}, as “apple” is the only element that exists in both set1 and set2.

The print(set1) statement will output {“apple”}.

The values True and 1 are considered the same value. The same goes for False and 0.

Difference

The difference() method will return a new set that will contain only the items from the first set that are not present in the other set.

You can use the – operator instead of the difference() method, and you will get the same result.

Note: The – operator only allows you to join sets with sets, and not with other data types like you can with the difference() method.

The difference_update() method will also keep the items from the first set that are not in the other set, but it will change the original set instead of returning a new set.

Symmetric Differences

The symmetric_difference() method will keep only the elements that are NOT present in both sets.

You can use the ^ operator instead of the symmetric_difference() method, and you will get the same result.

Note: The ^ operator only allows you to join sets with sets, and not with other data types like you can with the symmetric_difference() method.

The symmetric_difference_update() method will also keep all but the duplicates, but it will change the original set instead of returning a new set.

Dictionary Items

Dictionary items are ordered, changeable, and do not allow duplicates.

Dictionary items are presented in key:value pairs, and can be referred to by using the key name.

Ordered or Unordered?

As of Python version 3.7, dictionaries are ordered. In Python 3.6 and earlier, dictionaries are unordered.

When we say that dictionaries are ordered, it means that the items have a defined order, and that order will not change.

Unordered means that the items do not have a defined order, you cannot refer to an item by using an index.

Changeable

Dictionaries are changeable, meaning that we can change, add or remove items after the dictionary has been created.

Duplicates Not Allowed

Dictionaries cannot have two items with the same key:

Duplicate values will overwrite existing values:

Python – Access Dictionary Items

Accessing Items You can access the items of a dictionary by referring to its key name, inside square brackets:

Get Keys

The keys() method will return a list of all the keys in the dictionary.