Data Science Academy · 课时

添加、重命名和删除列

调整列的形状以适应分析

添加、重命名和删除列 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。

Shape Columns to Fit

Real analysis means reshaping columns: adding new ones, renaming unclear ones, and dropping clutter so your table answers the question at hand. ✂️

Add a Column by Assignment

Create a new column just by assigning to a fresh name. If it does not exist yet, pandas adds it on the spot.

df["total"] = df["price"] * df["qty"]

Derive From Other Columns

New columns often come from vectorized math on existing ones. Pandas applies the formula across every row at once, no loop needed.

Add a Constant Value

Assign a single value and pandas broadcasts it to every row. Handy for tagging a batch with a source label or a flag.

df["source"] = "web"

Rename for Clarity

The rename method swaps confusing headers for clear ones using a mapping dict. Good names make later code read like plain English.

df.rename(columns={"qty": "quantity"})

Rename Many at Once

Pass several pairs in the same dict to rename multiple columns in one call. Untouched columns simply keep their original names.

df.rename(columns={"qty": "quantity", "amt": "amount"})

Drop What You Do Not Need

The drop method removes columns by name. Use axis=1, or the clearer columns argument, to target columns rather than rows.

df.drop(columns=["notes"])

Drop Several Columns

Pass a list to drop to remove many columns in one go. Trimming dead weight keeps your table focused and faster to scan.

df.drop(columns=["notes", "temp"])

Most Methods Return a Copy

By default rename and drop return a new DataFrame and leave the original untouched. Capture the result to keep your changes.

df = df.drop(columns=["notes"])

Insert at a Position

Need a column in a specific spot, not the end? The insert method places it at the index you choose among the others.

df.insert(1, "rank", ranks)

Reorder by Selection

Reorder columns simply by selecting them in the order you want. A fresh column list gives you full control over layout.

df = df[["name", "total", "source"]]

Quick Check

Choose the method that removes a column from a DataFrame.

Recap: Column Surgery

Assign to add, rename to clarify, and drop to declutter. Reassign the result and your table fits the analysis perfectly. 🧩

常见问题解答

「添加、重命名和删除列」课时是免费的吗？

是的 — 「添加、重命名和删除列」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。

「添加、重命名和删除列」这节课中我会学到什么？

调整列的形状以适应分析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。

「添加、重命名和删除列」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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