modul_python (1).pptx for professional and student

Python
Introduction
Judul Agenda Bootcamp

Python
• Bahasa pemrograman tingkat
tinggi
• Penulisan kode/sintaks lebih
sederhana dan tersedia banyak
library
• Bersifat open-source dan cross-
platform
• Diluncurkan oleh Guido Van Rosum
pada tahun 1991.
• Data Analyst
• Data Engineer
• Data Scientist
• Business Intelligence
• ML Engineer
Data
Professional
• Cocok untuk pemula
• Sederhana tapi powerful
• High-demand skill
Pytho
n

Kenapa Python?
Freely usable including for
commercial purpose

Web apps, API
Executable
py2exe
pyinstaller
cx_freeze
Interpreter
Call within other PL

Python is easy to use (more concise)
versus
Bahasa C
#include <stdio.h>
int main() {
printf("Hello World!");
return 0;
}

Python Digunakan pada Beberapa Industri

Penerapan Python pada Proyek Data Science
Data
Exploratio
n
Data Pre-
Processin
g
Data
Cleansing
Data
Modeling
• Scraping, crawling, data mining
• Coding, query
• Seleksi fitur, statistika deskriptif, class balancing,
visualisasi data
• Transformasi fitur: Categorical encoding, binning
• Menangani nilai kosong (missing values), menghapu
terduplikasi
• Data formatting, menangani data pencilan (outliers)
• Melatih data dengan algoritma machine learning
• Melakukan klasifikasi, regresi, prediksi, klasterisasi
Pytho
n

Memulai Python
● Python adalah bahasa interpreter, yang dapat mengurangi siklus edit-test-
debug karena tidak memerlukan langkah kompilasi
● Untuk menjalankan Python, Anda memerlukan runtime/interpreter
environment untuk mengeksekusi kode:
• Mode interaktif: Setiap perintah yang Anda tulis akan
langsung ditafsirkan dan segera dieksekusi sehingga bisa
langsung melihat hasilnya 🡪 IPython
• Mode skrip: Anda memasukkan satu set kode Python ke
dalam format .py, program dijalankan baris demi baris
Python interpreter
.py
Hasil
outpu
t

Pilihan Development Environment
Pilih Development Environment yang paling mudah dan nyaman:
● Anaconda Distribution (https://www.anaconda.com/distribution/)
• Python, Conda, lebih dari 1000 library data science
● Miniconda (https://docs.conda.io/en/latest/miniconda.html)
• Python interpreter, Conda
● Jupyter Notebook (https://jupyter.org/)
● Python installer (https://www.python.org/downloads/).
● Google Colaboratory (https://colab.research.google.com/).

Anaconda Distribution
Anaconda Navigator
Sebuah aplikasi dashboard
interface pada paket
Anaconda Distribution

Jupyter Notebook
● Lingkungan pemrograman interaktif berbasis
web yang mendukung berbagai bahasa
pemrograman termasuk Python
● Banyak digunakan oleh peneliti dan akademisi
untuk pemodelan matematika, pembelajaran
mesin, analisis statistik, dan untuk pengajaran
pemrograman

Jupyter Notebook
● Skrip dapat ditulis dalam bentuk:
• Code : Algoritma dan formula matematis
• Markdown/Heading : Teks deskripsi, penjelasan code
• Raw NBConvert : Konversi format yang berbeda
● Hasil dapat diketahui langsung setelah menjalankan perintah Run

Google Colaboratory
● Skrip dapat ditulis dalam bentuk:
• Code : Algoritma dan formula matematis
• Teks: Teks deskripsi, penjelasan code
● Dapat digunakan pada https://colab.research.google.com/ dan hasil dapat diketahui
langsung setelah menjalankan perintah Run

First Python program
● The first thing to note, a Python code line that begins with a hash symbol will be considered
a comment, which will not be executed.

Syntax error message
● A mistake in writing down a Python command will yield an error message when executed.

Semantic error
● If there is a mistake in the program logic, Python will
not tell you a mistake if no syntax error is detected.
• E.g., suppose the intention is to print ‘Hello Python 101’, but
we accidentally write ‘Hello Python 102’, then Python won’t
complain although the code is wrong.

Outline
● Python: Overview
● Types, Expressions, Variables
● String operations
● Lists, Tuples
● Sets
● Dictionaries
● Conditions and Branching

Python types
Python types Example expression
int 11, -14, 0, 2
float 21.3201, 0.0, 0.8, -2.34
str “Hello Python 101”
boolean True, False
• Use type() function to get the
type of an expression

Typecasting: Convert one type to another

Boolean type
● Boolean type only has two
possible values: True and
False (with uppercase T and
F).
● The type name is bool
● Casting True to int yields 1
● Casting False to int yields 0

Expressions
● Expressions: operation that
Python performs
• E.g., arithmetic operation
● The symbols: +, -, *, /, //, etc.
are called operators
● The numbers are called
operands

Expressions
● Note that / and // are different

Expressions
● Python follows the traditional convention in operator precedence, e.g., multiplication is of
higher precedence than addition.
● Of course, parentheses takes highest precedence

Variables
● Variables store and give names to data values
● Variables do not have an intrinsic type; only data
values have it (int, float, str, bool, and many
others)
• Current type of a variable is the type of data value it currently
stores
● Data values are assigned to variables using ‘=‘
sign
• The statement/command is called variable assignment.
• A variable only stored the most recent data value assigned to
it.
● A data value assigned to a variable can be used in
any expression after the assignment by writing
that variable to the expression.

Examining types of variables
● We can use the type()command on variables to examine their
current types

Variable naming
● It’s good practice to use meaningful names for variables
• Variable names starts with a letter or underscore character (‘_’) followed by any number of letters or numbers.
● Suppose we have data about duration of three videos: 42 minutes, 57 minutes, and
43 minutes. How many hours of the total duration of three videos?

Ekspresi dengan Assignment Operator dan

print(____)
assignment
variable
value/nilai

Error/kesalahan:
- Lokasi kesalahan
- Jenis kesalahan
komentar

Comparison operators
Comparison
Operator
Operands
(Values) Boolean

Comparison: Equality
x == 8
5 Boolean

5 == 8? False

x == 8
8 Boolean

8 == 8? True

Comparison: Greater than, Less than, etc.
because 7 is greater than 6
because 6 is greater than or equal to 6
because 1 is less than 6,
i.e., NOT greater than or
equal to 6

Comparison: Greater than, Less than, etc.
because 1 is less than 6
because 1 is not equal to 6
because 1 is equal to 1

Comparing strings
● Two strings (or generally, sequences) A and B are the same if their length is
the same and for each position i, A[i] is equal to B[i].

The if Statement
● Suppose entrance to a tourist attraction is only given to those whose age is at most than 12 years old.
• E.g., if age is 13, 14, or more, then entrance is not granted and the person just moves on;
• if age is 12, 11, or less, then entrance is granted and (s)he moves on after enjoying the ride.
● We can write this branching using if statement
if CONDITION:
do_something_only_when_condition_holds
everyone_do_something
● After the if-condition, the statements that we want to execute only when the if-condition is true
MUST be written with an indentation!

The if Statement
Because 11 is less than or equal to 12,
if-condition holds
Because 13 is more than 12, the
indented statement is NOT executed.
Indented statements are executed when
the if-condition evaluates to true
This statement is executed regardless
whether the if-condition is true or not

The if-else statement: choosing one of two alternati
If-condition is True: 11 is less than or equal
to 12
If-condition is False: 13 is more than 12
This is executed
This is NOT executed
This is executed, regardless of the if-
condition
This is NOT executed
This is executed
This is executed, regardless of the if-condition
The else
statement

The elif statement: one of several alternati
The elif
statement
The condition is True (11 is less than or equal to 12)
Executed
NOT executed
This is always
executed

The elif
statement
if-condition is False: 13 is more than 12
Executed
NOT executed
This is always
executed
elif-condition is True,
13 is equal to 13

The elif
statement
if-condition is False: 13 is more than 12
Executed
NOT executed
This is always
executed
elif-condition is
False, 15 is not
equal to 13

The if, else, and elif statements
● Generally, we may have the following form:
• An if statement
• Followed by zero or more elif statements
• Then followed by zero or one else statement.
● The If-statement and all of elif statements have a Boolean condition
• The Boolean conditions are tested in turns from top to bottom until one condition
is found to be true.
• Once a true condition is found, the indented statements under the if/elif statement
for whose the condition is true are executed, and then we exit from the whole if-
elif-else block.
• If no condition is found to be true, and there is an else statement, then the
indented statements under it are executed. After that we exit the whole if-elif-else
block. If there is no else statement, we directly exit the if-elif-else block.

Exercise
● Create a program that accepts three integer inputs and then sorts them from smallest to
largest.

Functions
• Functions take some input and produce some output or change(s)
• It is simply a piece of code that can be reused.
• You can define your own function
• Or, more often, you simply use other people’s functions
• You just need to know how the function works (what’s the input and output)
• and sometimes, how to import the function to your program
Functions
Output
(value of b)
Output
(value of a)

Similar piece of code
Shorter main code Repeated similar parts are
separated as a function. The
main code sends a value to the
function and receives the
function return value.

Python built-in function example: len()
● len(Q)
• Q is a sequence (e.g., string, tuple, list, range) or a collection (e.g., set,
dictionary)
• Returns the length of Q, i.e., the number of elements it contains.

Python built-in function example: sum()
● sum(Q)
• Q is an iterable (e.g., tuple, list, set, etc.) containing numbers (or
anything that can be summed)
• Returns the sum of all elements in Q

Python builtin function example: sorted() and list.so
● sorted(Q)
• Q is an iterable (list, tuple, etc.)
• Returns a new list containing
the elements of Q in a sorted
order
• The elements must be things
that can be sorted, e.g.,
numbers, characters, strings
• Q itself does not change after
calling sorted().

Python builtin function example: sorted() and list.so
● If Q is a list and we wish
itself to be sorted, use
the list sort() method,
i.e., call Q.sort()
● Calling Q.sort() does not
return a new list, but
there is a change in Q
after the method call.

Making functions
Start with the keyword
def Function input given as variables called formal
parameters, written inside parentheses
Use a descriptive name
• add1 since we want to return the input
plus 1
Indented code block of
statements
Return the function result using keyword
return
After defining the function, we can call
it
Documentation string. Calling
help(add1) will yield this string.

Function: how does it work?
Variable c to be assigned the value of
add1(7). Function add1 is called with
argument value 7
7 is passed into the function as
parameter
Statements in the function run
with parameter variable a
replaced by 7
Return the value of b and
execute the assignment
def add1( ):
b = a + 1
7 + 1
8
return
a
c = add1( )
7
b
7
8
c:8
b

Function: variable scoping
● All variables defined inside a function, including parameter
variables are called local variables.
● Values are assigned to local variables only when the function is
called and they will be gone after exiting the function.
● In the next function call, those local variables are defined
again from scratch with possibly new values.

Function: variable scoping
● When line 5 is executed
• add1(a) is called with a assigned to 7
• Variable b becomes 8 and then 8 is
returned.
• Variable c is now assigned to 8 and values
of a and b are gone from the memory.
● Then, line 6 is executed.
• Process similar like above, but now with a
different value for variable a.
• Variable b is defined again, gets a
different value, and is returned.

Function can have multiple parameters
● Function my_mult multiplies both of its
arguments
● Function looks fine when given numbers
● Careful: my_mult doesn’t give an error
when arg1 is an integer and arg2 is a string
because multiplication can also mean
duplicating strings.
• Is this an intended behavior of my_mult?
• Needs to perform more testing to make sure
the function behaves as we intended.

Return statement is optional
● In a function execution, Python will exit from a function when
• a return statement is executed; or
• there is no more statement that can be executed
● So, functions can omit return statements
• e.g., when we simply want to print something or make some
changes to an object/data.

Return statement is optional
● In a function execution, Python will exit from a
function when
• a return statement is executed; or
• there is no more statement to be executed
● So, functions can omit return statements
• e.g., when we simply want to print something or
make some changes to an object/data.
● If a function exists NOT through a return
statement, Python will (silently) return an object
of type None to the caller.
● Function body cannot be empty
• a trivial function that returns None will have a pass
statement as its only statement.
• pass means “do nothing”.

Function can do multiple tasks
This function:
● prints a statement; and
● returns its argument
added by 2.

● Function can have all kinds of statements, such as loops.

Collecting arguments
We can define a function to receive varying
number of arguments (i.e., not fixed to one
argument or two argument in its definition).

Recursion
n=5
Factorial(n=5)
5 * Factorial(5-1)
4 * Factorial(4-1)
3 * Factorial(3-1)
2 * Factorial(2-1)
Factorial(1) 1
2
6
24
120
1
2
6
24
120

Lambda
• A lambda function is a small anonymous function.
• A lambda function can take any number of arguments, but can
only have one expression.

Exercise
● Create a function isPrime() to check whether a whole number is prime or not.

Strings
● String: sequence of characters enclosed within two double-quotes
● Can also be written by enclosing it within two single quotes.
● By default, Python interpreter outputs a string enclosed with single
quotes.

Strings
● Like other data values, we can assign a string to a variable
S e m a r a n g T a w a n g
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
• String is an ordered sequence,
• each element can be accessed via an index represented by an array of numbers
• Non-negative indices start from 0 going from left to right

Strings
● Negative index can also be used
• The rightmost index is -1, decreasing by 1 each time going from right to left
-15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1

String length
● Length of a string can be obtained via len() function

String slicing
● You can get a substring by slicing.
• s[m:n] is a substring of s taken from character at index m until character at index n-1
• If n m, maka hasil slicing adalah string kosong
≤
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
-15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1

String striding
● s[m:n:p] operates like s[m:n], but starting from index m, we move p steps at
a time from left to right
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
-15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1

String slicing and striding default value
● Omitting m, n, or p in the expression s[m:n] and s[m:n:p] causes Python to use their default values: m = 0, n = len(s), p = 1
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
-15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1

String concatenation
● We use “+” to concatenate strings

String replication
● Multiply a string with a number (using “*”) yields a new string containing the
replication of the old string.

Strings are immutable!
● String is immutable: you cannot change
the value of characters in a string.
• But you can reassign the variable
to a new string

String: sequence methods and string meth
● The previous methods/operations (indexing, slicing, striding) on
strings also work on other types of sequences (discussed later)
● Other than those, there are also methods specific to strings.
● Strings are immutable. So, we apply a method to a string A, the
method will return a new string B.
A Method B

String: Get uppercase version of a string
● upper() returns uppercase version of the string
upper()
A = “Surabaya is the city of heroes”
B: “SURABAYA IS THE CITY OF
HEROES”

String: replace substring with another
● Get a new string with the given
substring replaced by a new substring
A: “Jakarta is the largest”
“Jakarta is the largest”
B: “Jakarta is the most crowded”
most crowded

String: Find the occurrence of substring
● Find the location of the first occurrence of the given substring
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Ekspresi dengan operator pada string

String Operator “Is”
Boolean

Type for Tuple, Set, List, Dict

Tuples
● Tuple is an ordered sequence
● Tuples are written as comma-separated items within parentheses.
Its length is the number
of elements it contains

Tuples
● Tuples may contain elements of different types
str int float
• But the type of the sequence remains tuple

Tuple: accessing elements
0 “Alice”
1 85
2 3.8

Tuple: accessing elements (negative index
-3 “Alice”
-2 85
-1 3.8

Tuple concatenation
● Like string, tuple can be concatenated resulting in a new tuple.
0 1 2 3 4

Tuple slicing
● We can slice tuples like string
(‘Alice’, 85, 3.8, ‘USA’, 25)
0 1 2 3 4
0 1 2
3 4

Tuples are immutable (like strings)
(95, 85, 90, 72, 68, 82, 85, 90, 75)
grades
grades1

Tuples are immutable (like strings)
(95, 85, 90, 72, 68, 82, 85, 90, 75)
grade
s
grades
1
(95, 85, 90, 72, 68, 82, 85, 90, 75)
grade
s
grades
1
(90, 77, 88)
Changing the value of variable is simply changing
where the reference points to

Tuple nesting
● Tuples can be nested: a tuple may contain other tuples.
0 1 2 3 4

nt = (5, 7, ('Java', 'Bali'), (2, 11), ('Madura', (5, 7)))
0 1 2 3 4
('Java', 'Bali')
'Java' 'Bali'
nt[2][0] nt[2][1]
nt[2]
(2, 11)
2 11
nt[3][0] nt[3][1]
nt[3]
(‘Madura’, (5,7))
‘Madura' (5,7)
nt[4][0] nt[4][1]
nt[4]
'B’
'a’ 5 7
nt[2][1][0]
nt[2][1][1] nt[4][1][0]
nt[4][1][1]

Lists
● Lists are also ordered sequence, but mutable (unlike tuples or strings)
● Lists are written inside square brackets
● Lists can be nested, containing other lists
• In fact, lists and tuples can containing anything including lists and
tuples

Lists: Accessing elements
● Elements of lists can be accessed using index in the same way as tuples or strings.
L = ['Surabaya', 3.4, 1293]
0 1 2
-3 -2 -1

Lists are mutable
● Unlike tuples or strings, elements of a list can be changed.

Lists are mutable
● If a list is referenced by two variables, changing its elements via one variable
will cause the changes to be visible from the other variable.
Suppose we have L and LL as follows: We change L[1], and the change appear in LL too

List slicing
● Slicing works like in tuples, but returns a new list (not sharing reference
with the old one).
Lst[3] is changed
Lst35 includes element at Lst[3]
But, Lst35 is NOT changed!

List slicing
● Thus slicing can be used to copy a list
Lst_c is a copy of Lst
Lst[0] is changed
But Lst_c is NOT changed!

List: appending one element at the end
● append() adds just one
element to the end of the list.
● If its argument is another list,
then the old list now contains
a list as its last element.

List: deleting elements
● We can delete an element of a list at a particular index using del() function.

List concatenation: use ‘+’ operator
● Concatenating
two lists yields a
new list

List
Cek isi list
Tambah isi list

List: extending the list at the end
● If you want to lengthen the list with elements from another list, use extend() method.
• Lst is lengthened by adding to
its end as many positions as
the length of Lst2
• Elements of Lst2 are
successively copied to the
additional positions of Lst1

Convert string to list
● To convert a string (of words, separated by spaces) into a list of words,
we use the string method split()
● If we want, we can specify which character to be used as
separator/delimiter (instead of spaces).

Sets
● Sets: unordered mutable collection of unique elements
● (Like lists and tuples) Sets can store elements of any Python
types
● (Like lists and tuples) Sets are mutable
● (Unlike lists and tuples) Sets do not record element position
● (Unlike lists and tuples) Sets only contain unique elements –
duplicates are not stored.

Creating a set (1)
● Use curly brackets
• Notice that duplicates are not stored.

Creating a set (2)
• Or use the set() function
• Creating empty set can only be done using set() function, not curly braces!
Not a
set!

Set: adding elements
● Adding the same element doesn’t change the set
“Bandung”, “Bogor”,
“Depok”
“Bandung”, “Bogor”, “Depok”,
“Jakarta”
“Bandung”, “Bogor”, “Depok”,
“Jakarta”

Set: removing elements
“Bandung”,
“Bogor”, “Depok”
“Bandung”,
“Bogor”, “Depok”,
“Jakarta”

Set: check if the set contain the given elem
“Bandung”,

Set intersection
“Jakarta”
“Bandung”

Set intersection
“Bogor”,
“Depok”

Set union
“Jakarta”
“Bandung”

“Jakarta” “Bandung”
Set union
“Bogor”,
“Depok”

Subset test
“Jakarta”

Subset test
“Bogor”, “Depok”, “Jakarta”

Outline
● Loops
● Functions
● Reading and Writing Files
● Pandas
● Numpy Arrays

The range object constructor
1. range(stop)
• stop must be a positive integer, otherwise the range object is empty
• generates integers [0, 1, …, stop-1] length =
🡪 stop.
2. range(start, stop)
• start and stop must be integers
• start < stop must hold, otherwise the range object is empty
• generates integers [start, start + 1, …, stop] length =
🡪 stop – start
3. range(start, stop, step)
• start and stop must be integers and step must be nonzero integer
• if step > 0, then start < stop must hold, otherwise the range object is empty
• if step < 0, then start > stop must hold, otherwise the range object is empty
• generates integers [start, start + step, start + 2*step, …, start + k*step]
where k is the largest integer not exceeding (|stop – start|)/step.

Loops: for statements
● Suppose we are given a list of strings of color names, e.g.,
[“red”, “orange”, “green”, “purple”, “blue”]
● We wish to replace each color name with “black”, resulting in
[“black”, “black”, “black”, “black”, “black”]
● How do we do that?

colors = [“red”, “orange”, “green”, “purple”, “blue”]
0 1 2 3 4
for colors 0 in colors, colors 0 =
black
black
black
black
black
colors = [“black”, “orange”, “green”, “purple”, “blue”]
colors = [“black”, “black”, “green”, “purple”, “blue”]
colors = [“black”, “black”, “black”, “purple”, “blue”]
colors = [“black”, “black”, “black”, “black”, “blue”]
colors = [“black”, “black”, “black”, “black”, “black”]
• running index from 0 to 4
• each index value is used
to perform color name
change
• range(0,5) returns the
sequence [0, 1, 2, 3, 4]

Loop: for statement
● If we just want to use the value of each element in the list, but not changing
the list at all, we can even iterate on the elements directly (not using index)
Directly iterate on
elements of the list
color takes value of
“red”, then “orange”,
then “green”, and so
on

Loop: for statement
● We can also retrieve the index and the corresponding value simultaneously using
enumerate() function.
enumerate() takes the
list as the argument and
returning a sequence of
pairs.
Each pair consists of
index and the
corresponding element.
Each iteration uses one
pair at a time.

Loop: while statement
● For-loop runs a fixed number of iterations.
• The number of iterations is determined by the sequence of given in
the loop condition.
● While-loop runs as long as the loop condition remains True.
• The loop stops/terminates as soon as the loop condition becomes
False for the first time.

Loop: while statement
● Suppose we are given a list of color names (whose length and
content are unknown), e.g., orange, blue, purple, etc.
● Starting from the left, we want to copy all occurrences of
“orange” to a new list, but stop copying once a different color is
found.
• we don’t know how many “orange” color names are in the initial part of
the list, or whether there is any “orange” color name at all.
● How do we do it?

Suppose we copy from the list colors to oranges
• if colors is [“orange”, “orange”, “blue”, “orange”, “orange”, “orange”]
then oranges is [“orange”, “orange”]
• if colors is [“green”, “orange”, “orange”]
then oranges is []
We start from the left and check if the current color is orange.
If so, add it to the list oranges. Otherwise, stop copying.

• The while statement does not change the running index i automatically, so we
need to first initialize it (line 3) and increment it at every iteration (line 7).

Outline
● Python: Overview
● Types, Expressions, Variables
● String operations
● Lists, Tuples
● Sets
● Dictionaries
● Numpy Arrays

Dictionaries
● Dictionaries: a collection of pairs
• Each pair consists of a key followed by a value separated by a colon.
● A dictionary’s keys form a set:
• The keys are unique and immutable
• Position of keys in dictionary are not recorded
● Values may be immutable, mutable, and duplicates
● Denoted by a pair of curly brackets where each key-value pair
is separated by a comma from other key-value pairs.

Dictionary: analogy with list
● Dictionaries are similar to lists in the sense that we use arbitrary immutable objects as indices instead of
integers.
0 Element1
1 Element2
2 Element3
3 Element4
… …
Inde
x
Element
List
Key 1 Value 1
Key 2 Value 2
Key 3 Value 3
Key 4 Value 4
… …
Key: is an index by label Value
Dictionary

Dictionary
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9

Dictionary: accessing elements using key
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9

Dictionary: adding elements
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4

Dictionary: adding elements
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9

Dictionary: deleting elements
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4
“Jakarta” 10.1
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4

Dictionary: deleting elements
“Jakarta” 10.1
“Surabaya” 3.4
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4

Dictionary: check if element is in dictionary
“Jakarta” 10.1
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4

Dictionary: get all keys using keys() metho
“Jakarta” 10.1
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4
• keys() returns a list-like object containing
the dictionary’s keys (which can be
converted to a list or other collection

Dictionary: get all keys using keys() metho
“Jakarta” 10.1
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4

Dictionary: get all values using values() method
“Jakarta” 10.1
“Bogor” 1.1
“Depok” 1.8
“Bandung” 2.5
“Medan” 2.2
“Makassar” 1.4
“Denpasar” 0.9
“Ambon” 0.4
• values() method is similar, but for getting
all values in the dictionary

● Library dasar untuk perhitungan saintifik
(scientific computing) dengan Python (
https://numpy.org/)
● Alternatif untuk Python List: Numpy Array
untuk n-dimensi
● Mudah digunakan dan bersifat open source
● Jika library belum terpasang, tuliskan
perintah instalasi:
pip install numpy
● Kemudian impor:
import numpy as np
In [6]: import numpy as np
In [7]: np_height = np.array(height)
In [8]: np_height
Out[8]: array([1.84, 1.79, 1.82, 1.9, 1.8])
In [9]: np_weight = np.array(weight)
In [10]: np_weight
Out[10]: array([66.5, 60.3, 64.7, 89.5, 69.8])
In [11]: bmi = np_weight / np_height ** 2
In [12]: bmi
Out[12]: array([19.64201323, 18.81963734,
19.53266514, 24.79224377, 21.54320988])

● NumPy juga dapat digunakan untuk
membuat array berdimensi-n
In [13]: import numpy as np
In [14]: np_height = np.array([1.84, 1.79, 1.82,
1.9, 1.8])
In [15]: np_weight = np.array([66.5, 60.3, 64.7,
89.5, 69.8])
In [16]: type(np_height)
Out[16]: numpy.ndarray
In [16]: type(np_weight)
Out[16]: numpy.ndarray
ndarray = n-dimensional array
1 2 3 4 5
6 7 8 9 10
M =

● NumPy dapat digunakan untuk membuat
array artifisial dengan method arange()
dan linspace()

Objects in Python
Objects are specific instances of a class
Apple Samsung
Motorola

Different Object and Function
1. Menggunakan Fungsi
2. Menggunakan Class
1. Simple
2. Harus secara manual pass dan return balance
setiap waktu
3. Balance di simpan di luar fungsi
1. Status Balance disimpan di dalam object
2. Lebih intuitif untuk pemodelan dunia nyata

168
Creating the first Class
Creating the ‘Phone’ class
Instantiating the ‘p1’ object
Invoking methods through
object

169
Adding parameters to the class
Setting and Returning
the attribute values
Special Method: __init__, __str__,and __repr__

170
Creating a class with Constructor
init method acts as the constructor
__init__ is a method that is
automatically called when
memory is allocated to a new
object.
For invoking in build parameter with object , self is
used .

171
Instantiating Object & Special Method
Instantiating the ‘e1’ object
Invoking the
‘employee_details’
method
Special Method: _ __str__and __repr__
__str__: Output when do print(obj)
__repr__: Output in debugging/console

172
Inheritance in Python
With inheritance one class can derive the properties of another class
Man inheriting
features from his
father

173
Inheritance Example
Creating the base
class
Instantiating the object for base
class

174
Inheritance Example
Creating the child
class
Instantiating the object for child
class
Invoking the child class
method

175
Overriding init method
Overriding init method
Invoking show_details()
method from parent
class
Invoking
show_car_details() method
from child class

Exercise
1
2
Buat class User dengan atribut: name, email
Tambahkan method greet() yang mengembalikan string
sapaan
Tambahkan __str__() untuk output readable
Buat class Admin yang mewarisi User
Tambahkan atribut level dan method promote()

Terimakas
ih
Dank
e
Gracia
s
Thank
you
Grazie
Arigat
ou
Merc
i
Syukro
n
Obriga
do
Gamsa
Hamnida
Xie-
Xie
Kheilil
Mamnun

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