13 Data Types in Python

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In the context of data science, you often work with various data types and structures to analyze, manipulate, and visualize data. Here’s a list of data types commonly used in data science:

1. Numeric Types:

• int: Integer (representing whole numbers)
• float: Floating-point or Decimal (representing real numbers)

2. Text Type:

• str: String (representing text data)

3. Boolean Type:

• bool: Boolean (representing True or False)

4. Sequence Types:

• list: List (ordered, mutable) (used for storing ordered collections)
• tuple: Tuple (ordered, immutable) (used for representing fixed collections)
• range: Range of numbers (used for iterating over a sequence of numbers)

5. Set Types:

• set: Set (unordered, mutable, unique elements) (used for storing unique values)

6. Mapping Type:

• dict: Dictionary (unordered, mutable, key-value pairs) (used for storing key-value associations)

7. Text Sequence Types:

• str: String (used for text data)