Lesson 3: Pandas DataFrames – The Heart of Data Tables

1. What is a DataFrame?

A DataFrame is a 2D table with rows & columns — like Excel or SQL table.

Each column is a Series → same power + table structure.

import pandas as pd

data = {
    "name": ["Alice", "Bob", "Charlie"],
    "age": [25, 30, 35],
    "city": ["NY", "LA", "SF"]
}
df = pd.DataFrame(data)
print(df)

Rows indexed 0,1,2; columns: name, age, city.

2. Accessing & Modifying DataFrames

• Column: df["age"] or df.age
• Row: df.loc[1] (label) or df.iloc[1] (position)
• Cell: df.loc[1, "city"] or df.at[1, "city"]
• Add column: df["country"] = "USA"
• Drop column: df.drop("country", axis=1)

axis=0 = rows, axis=1 = columns.