按键和索引合并
按列或按索引连接
按键和索引合并 是 CoddyKit 上的免费 Data Science Academy 课时。 这是第 2 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。
Same Name, One Word
When both tables share a column with the same name, on is all you need to merge them together.
orders.merge(customers, on="customer_id")Join on Many Keys
Sometimes one column is not enough. Pass a list to on and pandas matches rows on every key at once.
sales.merge(targets, on=["region", "month"])Different Names, No Problem
When key columns are named differently, use left_on and right_on to tell pandas which column maps to which.
orders.merge(users, left_on="uid", right_on="id")A Leftover Column
With left_on and right_on, both key columns survive in the result. You often drop the duplicate afterward.
merged.drop(columns="id")The Index Can Be a Key Too
If your key lives in the index instead of a column, set left_index or right_index to True to join on it.
orders.merge(prices, left_on="sku", right_index=True)join for Index Merges
For two index-aligned tables, the join method is shorter. It merges on the index by default.
left.join(right)Handle Overlapping Names
When both tables have a column with the same name, pandas adds suffixes so the two versions stay distinct.
a.merge(b, on="id", suffixes=("_a", "_b"))Keys Must Share a Type
A common surprise: a key stored as a string on one side and an integer on the other will simply never match.
Mind Duplicate Keys
If a key value repeats on both sides, merge produces every matching pair. Rows can multiply unexpectedly.
join Defaults to Left
Unlike merge, the join method uses a left join by default. Pass how to change it when you need to.
left.join(right, how="outer")Pick the Right Tool
Use merge for column keys with full control, and join when both tables are already aligned on their index. 🔧
Quick Check
Your key columns have different names in each table. What do you use?
Recap: Matching the Keys
You can merge on shared columns, mismatched names, or the index, and use suffixes to keep overlapping columns clear. Nicely done!
常见问题解答
「按键和索引合并」课时是免费的吗？
是的 — 「按键和索引合并」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。
「按键和索引合并」这节课中我会学到什么？
按列或按索引连接 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 2 节课，共 4 节。
「按键和索引合并」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。