python

🔶 Pandas: Pivot Tables and Reshaping

# pivot_table = aggregate + reshape (like Excel pivot)
pd.pivot_table(df,
    values='sales',
    index='region',
    columns='quarter',
    aggfunc='sum'
)

# melt = opposite of pivot (wide → long)
pd.melt(df,
    id_vars=['name'],
    value_vars=['Q1', 'Q2', 'Q3'],
    var_name='quarter',
    value_name='sales'
)

When to use pivot: When you want to see a metric across two dimensions (region × quarter). When to use melt: When your columns ARE data (Q1, Q2, Q3 are values of "quarter") and you need them as rows for analysis or plotting.