Introduction to Python Programming for Data Science

Python Programming

Key Concepts

Displaying Output
- Use the print() function to display the result of code execution:
```
print(1 + 2)   # Outputs: 3
print(5 * 10)  # Outputs: 50
```

Using Comments

Comments start with # and are ignored by the computer:

# print(1 + 2)  # This line is ignored
print(5 * 10)  # Outputs: 50

Arithmetic Operations

Python supports basic arithmetic:

+ 2       # Addition
- 5       # Subtraction
* 12     # Multiplication
/ 3     # Division
** 3      # Exponentiation
(4 * 18) ** 2 / 10  # Complex expressions

Programming Basics
- Programming: Writing a set of instructions for the computer.
- Code: The instructions written in a programming language.
- Program: A collection of code that performs a task.

Code Syntax

Python has strict syntax rules. For example:

print(23 + 7)  # Correct
print(10 - 6) print(12 + 38)  # Incorrect, causes a syntax error

Input and Output
- Input: Code written as instructions for the computer.
- Output: Results produced by executing the code.
Code Comments
- Comments explain the code or disable certain lines from executing.
- Example:
```
# This is a comment
print("Hello, World!")  # Prints a greeting
```

Summary

print() displays program output.
# comments are ignored during execution.
Programming involves writing code that instructs the computer to perform tasks.
Follow Python syntax rules to avoid errors.

Additional Resources

Dataquest Python Learning Modules

Programming Python Variables

Key Points

Storing Values in Variables

twenty = 20
result = 43 + 2**5
currency = 'USD'

Updating Variable Values
```
x = 30
x += 10  # Same as x = x + 10
```

Syntax Shortcuts

Common shorthand operations:

x += 2  # Addition
x -= 2  # Subtraction
x *= 2  # Multiplication
x /= 2  # Division
x **= 2 # Exponentiation

Variable Naming Rules
- Use only letters, numbers, or underscores.
- Do not start a variable name with a number.
Assignment Operator (=)
- The = operator assigns a value to a variable.
```
x = 5  # Read as "x is assigned the value 5"
```
- It does not denote equality.
Error Types
- Syntax Error: Code structure is invalid.
- Runtime Error: Code syntax is correct, but execution fails.
Data Types
- Data types classify values, determining how the computer processes, stores, and operates on them.

Concepts Learned

Variables are storage locations in memory.
The = operator is an assignment operator, not a symbol of equality.
Syntax shortcuts simplify arithmetic operations.

Additional Resources

Dataquest Python Learning Modules

Python Data Types: Integers, Floats, Strings

Key Points

Rounding a Number
```
round(4.99)  # Output: 5
```
Creating Strings
- Using quotation marks to define strings:
```
app_name = "Clash of Clans"
app_rating = '3.5'
```

Concatenating Strings

Combining two or more strings:

print('a' + 'b')      # Output: 'ab'
print('a' + 'b' + 'c')  # Output: 'abc'

Type Conversion

Converting between data types:

int('4')      # Converts string to integer
str(4)        # Converts integer to string
float('4.3')  # Converts string to float
str(4.3)      # Converts float to string

Finding the Type of a Value

type(4)      # Output: <class 'int'>
type('4')    # Output: <class 'str'>

Concepts Learned

Data Types: Introduced integers, floats, and strings.
String Concatenation: Linking two or more strings.

Additional Resources

Python Lists

Key Points

Creating a List of Data Points

row_1 = ['Facebook', 0.0, 'USD', 2974676, 3.5]
row_2 = ['Instagram', 0.0, 'USD', 2161558, 4.5]

Creating a List of Lists
```
data = [row_1, row_2]
```

Retrieving Elements from a List

Access specific elements using index notation:

first_row = data[0]                       # First list in data
first_element_in_first_row = first_row[0] # 'Facebook'
last_element_in_first_row = first_row[-1] # 3.5
# Shortcut for nested lists:
first_element_in_first_row = data[0][0]   # 'Facebook'
last_element_in_first_row = data[0][-1]   # 3.5

Creating a New List from Elements

Extract elements to form a new list:

row_1 = ['Facebook', 0.0, 'USD', 2974676, 3.5]
rating_data_only = [row_1[3], row_1[4]]   # [2974676, 3.5]

List Slicing

Extract a range of elements:

row_1 = ['Facebook', 0.0, 'USD', 2974676, 3.5]
second_to_fourth_element = row_1[1:4]    # [0.0, 'USD', 2974676]

Key Concepts
- Data Point: A single value providing information.
- Dataset: A collection of data points (e.g., tables).
- Lists: A Python data type used to store datasets.

Summary

Python lists can store individual data points or datasets like tables.
You can access, slice, or manipulate list elements using indexing and slicing.
Lists are versatile for working with data collections in Python.