Lesson 2: Pandas Series – Understanding 1D Data

1. What is a Series?

A Series is a one-dimensional labeled array — like a column in Excel.

Each value has an index (label) — more powerful than Python lists.

import pandas as pd

ages = pd.Series([25, 30, 35, 40], index=["Alice", "Bob", "Charlie", "David"])
print(ages)

Output:

Alice      25
Bob        30
Charlie    35
David      40
dtype: int64

2. Series Operations

• Math: s + 5, s * 2
• Filtering: s[s > 30]
• Methods: .mean(), .sum(), .max(), .min(), .value_counts()
• Missing values: NaN (not a number)

Example:

s = pd.Series([10, 20, None, 40])
s.mean()  # 23.333 (ignores NaN)