标签、标题和图例
让图表真正清晰易读
标签、标题和图例 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。
A Chart Must Explain Itself
An unlabeled plot is a riddle. Good labels let a reader understand it in seconds without asking you a single question. 🏷️
Give It a Title
Add a clear headline with plt.title that states the chart message, like Monthly Sales by Region.
plt.title("Monthly Sales by Region")Name the X Axis
Label the horizontal axis with plt.xlabel so readers know what each tick along the bottom represents.
plt.xlabel("Month")Name the Y Axis
Use plt.ylabel to say what the height measures, and include the unit, like Sales in dollars.
plt.ylabel("Sales ($)")Add a Legend
When several lines share a chart, a legend maps each color to its meaning so nobody has to guess.
plt.legend()Legends Need Labels
The legend only works if each series has a label. Pass label= in every plot call, then call legend once.
plt.plot(x, y, label="North")Rotate Crowded Ticks
Long category names overlap and become unreadable. Rotate them upright with xticks and a rotation angle.
plt.xticks(rotation=45)Place the Legend
If the legend covers your data, move it. Pass loc like "upper left" to send it to a clearer corner.
plt.legend(loc="upper left")Tidy the Layout
Labels sometimes spill off the edge. Call plt.tight_layout to nudge everything into the figure neatly.
plt.tight_layout()Order of Calls Matters
Add titles and labels after you draw and before you show. matplotlib applies them to the current active axes.
Save the Finished Chart
Share your work by writing it to a file with savefig, choosing a clear name and a sharp resolution.
plt.savefig("sales.png", dpi=150)Quick Check
Two lines on one chart and nobody knows which is which. What did you forget?
Recap: Polish That Plots Earn
You now add a title, axis labels, and a legend, rotate ticks, and save the result. Your charts finally explain themselves! ✨
常见问题解答
「标签、标题和图例」课时是免费的吗？
是的 — 「标签、标题和图例」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。
「标签、标题和图例」这节课中我会学到什么？
让图表真正清晰易读 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。
「标签、标题和图例」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。