按名称选择列
单列和列列表
按名称选择列 是 CoddyKit 上的免费 Data Science Academy 课时。 这是第 1 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。
Columns Are Your Starting Point
Real datasets have dozens of columns, but you rarely need them all. Picking the right columns by name is the first move in almost every analysis. 🎯
Grab One Column
To pull a single column, put its name in square brackets after the DataFrame. What you get back is a one-dimensional Series.
ages = df["age"]
print(ages.head())A Single Column Is a Series
One bracketed name returns a Series: a single labeled column, not a table. It keeps the same index as the DataFrame it came from.
type(df["age"])
# pandas.core.series.SeriesDot Access as a Shortcut
You can also reach a column with dot access, like df.age. It is shorter, but only works when the name has no spaces or symbols.
df.age # same as df["age"]When Dot Access Fails
Dot access breaks on names with spaces, like df.user name, or names that clash with methods. When in doubt, prefer bracket access for safety.
df["user name"] # brackets handle spacesSelect Several Columns
Pass a list of names inside the brackets to grab many columns at once. Notice the double square brackets in the syntax.
subset = df[["name", "age", "city"]]A Column List Is a DataFrame
Selecting a list of names returns a DataFrame, even if the list holds just one name. That is the key difference from single-bracket access.
df[["age"]] # DataFrame, not SeriesOrder Is Up to You
The columns appear in the exact order you list them, not their original order. This is a quick way to rearrange a table for a report.
df[["city", "name"]] # city first nowSelecting Many With loc
The loc accessor selects by label and lets you choose rows and columns together. A colon means all rows.
df.loc[:, ["name", "age"]]List All Column Names
Forgot the exact spelling? The columns attribute lists every name, so you can copy them without typos.
print(df.columns.tolist())Watch the KeyError
Ask for a name that does not exist and pandas raises a KeyError. Names are case-sensitive, so Age and age are different.
df["Age"] # KeyError if column is "age"Quick Check
Think about what each bracket style returns.
Recap: Picking Columns
Single brackets give a Series, a list of names gives a DataFrame in your chosen order, and loc selects by label. You now grab exactly the columns you need. ✅
常见问题解答
「按名称选择列」课时是免费的吗？
是的 — 「按名称选择列」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。
「按名称选择列」这节课中我会学到什么？
单列和列列表 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 1 节课，共 4 节。
「按名称选择列」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。