Data Science & Machine Learning

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Now, let's move to the next topic of Data Science Roadmap: ✅ Python Dictionaries 📚 Dictionaries are one of the most important data structures in Python, especially in data science and real-world datasets. They store data in key–value pairs. 🔹 1. What is a Dictionary? A dictionary stores data in key:value format. ✅ Example:

student = { "name": "Rahul", "age": 22, "course": "Data Science" }
print(student)

Output: {'name': 'Rahul', 'age': 22, 'course': 'Data Science'} ✔ Uses curly brackets {} 🔹 2. Access Dictionary Values Use the key to access values.

student = { "name": "Rahul", "age": 22 }
print(student["name"])

Output: Rahul 🔹 3. Add New Elements

student = { "name": "Rahul", "age": 22 }
student["city"] = "Delhi"
print(student)

Output: {'name': 'Rahul', 'age': 22, 'city': 'Delhi'} 🔹 4. Modify Values

student["age"] = 23

🔹 5. Remove Elements

student.pop("age")

🔹 6. Important Dictionary Methods ⭐ ✅ Get Method:

print(student.get("name"))

Output: Rahul ✅ Keys Method:

print(student.keys())

Output: dict_keys(['name', 'age']) ✅ Values Method:

print(student.values())

Output: dict_values(['Rahul', 22]) ✅ Items Method:

print(student.items())

Output: dict_items([('name', 'Rahul'), ('age', 22)]) 🔹 7. Loop Through Dictionary

student = { "name": "Rahul", "age": 22 }

for key, value in student.items():
    print(key, value)

Output: name Rahul age 22 🎯 Today’s Goal ✔ Understand key–value pairs ✔ Access dictionary values ✔ Add or update data ✔ Loop through dictionary 👉 Dictionaries are widely used in APIs, JSON data, and machine learning datasets. Double Tap ♥️ For More

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Data Science Roadmap ✅ Conditional Statements (if–else) 🐍⚡ Conditional statements allow programs to make decisions based on conditions. 👉 Used heavily in: ✔ Data filtering ✔ Business rules ✔ Machine learning logic 🔹 1. if Statement Used to execute code when a condition is True. ✅ Syntax

if condition:
    # code

Example

age = 20
if age >= 18:
    print("You can vote")

# Output: You can vote 🔹 2. if–else Statement Used when there are two possible outcomes. Syntax

if condition:
    # code if true
else:
    # code if false

Example

age = 16
if age >= 18:
    print("Eligible to vote")
else:
    print("Not eligible")

🔹 3. if–elif–else Statement Used when there are multiple conditions. Syntax

if condition1:
    # code
elif condition2:
    # code
else:
    # code

Example

marks = 75
if marks >= 90:
    print("Grade A")
elif marks >= 60:
    print("Grade B")
else:
    print("Grade C")

🔹 4. Nested if Statement An if statement inside another if.

age = 20
citizen = True
if age >= 18:
    if citizen:
        print("Eligible to vote")

🔹 5. Short if (Ternary Operator)

age = 20
print("Adult") if age >= 18 else print("Minor")

🎯 Today’s Goal ✔ Understand if ✔ Use if–else ✔ Use elif for multiple conditions ✔ Learn nested conditions 👉 Conditional logic is used in data filtering and decision models. Double Tap ♥️ For More

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✅ Python Functions 🐍⚙️ Functions are very important in data science. They help you write reusable, clean, and modular code. 🔹 1. What is a Function? A function is a block of code that performs a specific task. 👉 Instead of writing the same code again and again, we create a function. 🔥 2. Creating a Function ✅ Basic Syntax

def function_name():
    # code

✅ Example

def greet():
    print("Hello Deepak")
greet()

Output: Hello Deepak 🔹 3. Function with Parameters Parameters allow input to functions.

def greet(name):
    print("Hello", name)
greet("Rahul")

# Output: Hello Rahul 🔹 4. Function with Return Value (Very Important ⭐) Instead of printing, functions can return values.

def add(a, b):
    return a + b
result = add(5, 3)
print(result)

# Output: 8 👉 return sends value back. 🔹 5. Default Parameters

def greet(name="Guest"):
    print("Hello", name)
greet()
greet("Amit")

🔹 6. Why Functions Matter in Data Science? ✅ Data cleaning functions ✅ Feature engineering functions ✅ Reusable ML pipelines ✅ Code organization 🎯 Today’s Goal ✔ Understand def ✔ Use parameters ✔ Use return ✔ Call functions properly Double Tap ♥️ For More

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