Filter DataFrames with Multiple Conditions in Pandas

Question

Given an e-commerce `orders_df`, filter for orders where `category == 'Electronics'`, `status == 'Delivered'`, and `total_amount >= 5000`.

Accepted Answer

Optimal Solution:
import pandas as pd

# Bitwise & with mandatory parentheses around each condition
filtered_df = orders_df[
    (orders_df['category'] == 'Electronics') &
    (orders_df['status'] == 'Delivered') &
    (orders_df['total_amount'] >= 5000)
]

Technical Explanation:
Pandas overrides bitwise `&` (AND) and `|` (OR) for element-wise boolean series evaluation. Python's operator precedence rules require parentheses around each equality condition.

order_id	category	status	total_amount
101	Electronics	Delivered	6500
102	Electronics	Cancelled	8000
103	Fashion	Delivered	5500
104	Electronics	Delivered	3200