Pandas Pivot Tables

Aggregate and reshape multidimensional data using pivot_table.

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A pivot table is a data summarization tool that groups data and performs aggregations (like sum, mean, or count) across specified index rows and column dimensions.

Key Takeaways: Pandas Pivot Tables

Mastering Pandas Pivot Tables helps you write clean and reliable Pandas code. Follow standard conventions, test edge cases, and keep logic simple. Try running the code example below and complete the exercises to build confidence.

Pandas Pivot Tables Code Example

Pandas

import pandas as pd

df = pd.DataFrame({
    "Region": ["North", "North", "South", "South"],
    "Product": ["A", "B", "A", "B"],
    "Sales": [100, 150, 200, 250]
})
pivot = df.pivot_table(values="Sales", index="Region", columns="Product", aggfunc="sum")
print(pivot)

Output

Product    A    B
Region            
North    100  150
South    200  250

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Pandas Pivot Tables

💡 Key Takeaways: Pandas Pivot Tables

Pandas Pivot Tables Code Example

Key Takeaways: Pandas Pivot Tables