Ranking Methods in Pandas: min, max, first, dense

Question

Given duplicate salary values, compute rankings using `method='dense'` and `method='min'`. Explain how each handles ties.

Accepted Answer

Optimal Solution:
import pandas as pd

df['rank_dense'] = df['salary'].rank(method='dense', ascending=False).astype(int)
df['rank_min'] = df['salary'].rank(method='min', ascending=False).astype(int)

result_df = df

Technical Explanation:
`method='dense'` behaves like SQL DENSE_RANK (ties get same rank, next rank is +1: 1, 2, 2, 3). `method='min'` behaves like SQL RANK (ties get same rank, but next rank is skipped: 1, 2, 2, 4).

name	salary
Aarav	100
Bhavna	90
Chirag	90
Divya	80

name	salary	rank_dense	rank_min
Aarav	100	1	1
Bhavna	90	2	2
Chirag	90	2	2
Divya	80	3	4