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Practice

Introduction to Pandas and DataFrames

Pandas is one of the most powerful and widely used Python libraries for data analysis.

It helps you organize, clean, and explore information in a structure similar to Excel or Google Sheets — but with the full flexibility and efficiency of Python.

Instead of writing loops or complex logic, you can manage and transform data using concise, readable commands.

The two main structures you'll use in Pandas are:

  • Series: a one-dimensional list with labels
  • DataFrame: a two-dimensional table, similar to a spreadsheet

DataFrame​

A DataFrame is the core data structure in Pandas — a labeled, two-dimensional table with rows and columns.

Below is an example of creating a simple DataFrame from a dictionary.

Preview: Creating a Simple DataFrame
import pandas as pd

# Create a small DataFrame from a dictionary
data = {
    "Name": ["Alice", "Bob", "Charlie"],
    "Age": [25, 30, 22]
}

df = pd.DataFrame(data)

print(df)
# Output:
#   Name  Age
# 0  Alice   25
# 1    Bob   30
# 2 Charlie   22

Series​

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