Data Types and Type Conversion in Python

1. Introduction to Data Types

Variables store values, and those values have data types.

Common data types in Python:

• String (str) → text
• Integer (int) → whole numbers
• Float (float) → decimal numbers

Key Point:
Data types define what kind of data a variable holds

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2. String (Text Data)

A string is a sequence of characters.

• Written using:
  • Single quotes ' '
  • Double quotes " "
• Represents textual information

Example:

• "hello"
• 'data science'

Important Property:

• Strings are immutable
  • Cannot be changed after creation

Key Point:
Strings = text data, cannot be modified directly

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3. Integer (Whole Numbers)

An integer represents whole numbers.

Examples:

• 1, 10, 100

No decimals allowed

Key Point:
Integers = whole numbers only

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4. Float (Decimal Numbers)

A float represents numbers with decimals.

Examples:

• 2.5, 3.14, 0.99

Key Point:
Floats = numbers with fractional parts

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5. Mixing Data Types (Common Errors)

Computers usually cannot combine different data types directly.

Example:

• Integer + String → ❌ Error

This produces a TypeError

Example concept:

• 7 + "8" → error

Key Point:
Different data types must be compatible

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6. Understanding Errors

Errors provide useful information.

• Example: TypeError
  • Occurs when incompatible types are used together

Strategy:

• Read error message carefully
• Use it as a clue to fix code

Key Point:
Errors are learning tools

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7. Checking Data Type

Use the type() function to identify a value’s type.

Examples:

• type("A") → string
• type(2) → integer
• type(2.5) → float

Key Point:
Always check data type before operations

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8. Class and Data Type

• In Python, data type = class
• A class defines:
  • Data
  • Behavior

Examples:

• String → str class
• Integer → int class

Key Point:
Every value belongs to a class

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9. Implicit Conversion (Automatic)

Python sometimes converts data types automatically.

Example:

• Integer + Float → Float

Python converts integer → float automatically

Key Point:
Implicit conversion happens in the background

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10. Explicit Conversion (Type Casting)

You can manually convert data types.

Common functions:

• int() → convert to integer
• float() → convert to float
• str() → convert to string

Example:

• Convert number → string

This is called typecasting

Key Point:
Explicit conversion = user-controlled conversion

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11. Why Type Conversion is Important

In data analysis:

• Data comes in different formats
• Must convert types to:
  • Combine data
  • Perform calculations

Key Point:
Type conversion enables data integration

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12. Debugging Skills

Debugging = finding and fixing errors

Important habits:

• Read error messages carefully
• Understand cause
• Search online when needed

Key Point:
Even experts use online resources

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13. Practical Insight

• Programs often:
  1. Receive input
  2. Process data
  3. Store result

Variables + data types = core of this process

Key Point:
Understanding data types is essential for real-world coding

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Final Summary

Python uses different data types such as strings, integers, and floats to represent different kinds of data. Mixing incompatible types can cause errors, so it is important to understand and check data types using the type() function. Python supports both implicit and explicit type conversion, allowing flexible data handling. Mastering data types and conversions is essential for data analysis and debugging.

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Key Takeaways

• String = text (immutable)
• Integer = whole number
• Float = decimal number
• Mixing types can cause errors
• Use type() to check data types
• Implicit conversion = automatic
• Explicit conversion = manual (typecasting)
• Debugging is a key skill
• Data type understanding is essential for data work