LM Object Data Types

Object Data Types (Lists, Arrays, DataFrames)

Python offers various complex data types to store collections of data:

  • Lists: Ordered, mutable collections of items
  • Arrays: More efficient arrays of homogeneous data, often using numpy
  • DataFrames: Tabular data structures from the pandas library, ideal for data analysis

Mastering these types allows you to work efficiently with larger and more complex data sets.

Examples

# List example
fruits = ["apple", "banana", "cherry"]
fruits.append("orange")
print(fruits)

# Array example (requires numpy)
import numpy as np
numbers = np.array([1, 2, 3, 4])
print(numbers * 2)

# DataFrame example (requires pandas)
import pandas as pd
data = {
    "Name": ["Alice", "Bob", "Charlie"],
    "Age": [25, 30, 35]
}
df = pd.DataFrame(data)
print(df)

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