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stack、unstack 和 MultiIndex

重塑层次化表格

stack、unstack 和 MultiIndex 是 CoddyKit 上的免费 Data Science Academy 课时。这是第 4 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Data Science Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Data Science Academy 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Reshaping With the Index

Beyond melt and pivot, pandas can reshape using the index itself. The tools are stack and unstack on hierarchical labels. 🏗️

What a MultiIndex Is

A MultiIndex stacks two or more label levels on one axis, so a single row can carry both a region and a year together.

stack Pushes Columns Down

stack moves the innermost column level into the row index, making the table taller and narrower in one move.

df.stack()

unstack Pulls Rows Up

unstack is the reverse: it lifts an index level back into columns, making the table wider and shorter again.

df.unstack()

They Undo Each Other

Stack then unstack returns the original shape. Think of them as a paired toggle between row labels and column labels.

Pick a Level to Move

Pass a level name or number to choose which one shifts. This level control lets you reshape exactly the axis you mean.

df.unstack(level='year')

Selecting From a MultiIndex

Use loc with a tuple to drill into nested labels, grabbing one region-year combination directly from the stacked index.

df.loc[('West', 2021)]

Cross-Section With xs

The xs method slices one level cleanly, like every row for year 2021, without unpacking the whole index by hand.

df.xs(2021, level='year')

Flatten When You Are Done

To return to plain columns, call reset_index. It turns every index level back into an ordinary, exportable column.

df.reset_index()

Stack Drops NaN by Default

By default stack quietly removes missing combinations. Set dropna to False when you need to keep every gap visible.

df.stack(dropna=False)

Where This Fits

groupby with several keys returns a MultiIndex, so unstack is the natural finishing move to spread those groups into a grid.

Quick Check

Last check: stacking and unstacking.

Recap: You Can Reshape Anything

You now wield pivot_table, melt, stack, and unstack. With layout under control, your analysis stays clean and flexible. 🎉

常见问题解答

「stack、unstack 和 MultiIndex」课时是免费的吗？

是的 — 「stack、unstack 和 MultiIndex」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Data Science Academy 课程的其余内容，请升级到 CoddyKit PRO。 Data Science Academy 课程共包含 4 节课。

「stack、unstack 和 MultiIndex」这节课中我会学到什么？

重塑层次化表格你通过在浏览器中直接运行的动手代码来练习 Data Science Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Data Science Academy 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Data Science Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 4 节课，共 4 节。

「stack、unstack 和 MultiIndex」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Data Science Academy 课中编写并运行代码吗？

能。每节 Data Science Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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