Top N Values

Finding the largest or smallest values is a common operation. Pandas provides efficient methods for this.

nlargest() and nsmallest()

Get the top or bottom N rows:

vs. sort_values().head()

nlargest and nsmallest are more efficient:

Multiple Columns

Specify tie-breaker columns:

Series nlargest/nsmallest

Also works on Series:

Combining with Other Operations

Find top N within groups or after filtering:

Using idxmax() and idxmin()

Find the index of max/min values:

Exercise: Top Products

Exercise: Find Maximum

Key Points

• nlargest(n, column) gets top N rows
• nsmallest(n, column) gets bottom N rows
• More efficient than sort_values().head()
• Works on both DataFrames and Series
• idxmax() / idxmin() find index of max/min
• Can use multiple columns for tie-breaking