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matplotlib 中的折线图和条形图

直接从 DataFrame 绘图

matplotlib 中的折线图和条形图 是 CoddyKit 上的免费 Data Science Academy 课时。这是第 3 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。

Pictures Beat Tables

A wall of numbers hides trends. A quick chart reveals them instantly, which is why every analysis ends with a plot. 📊

Import pyplot Once

The drawing engine lives in matplotlib.pyplot, almost always imported as plt. That short alias keeps every plot call tidy.

import matplotlib.pyplot as plt

Line Charts Show Change

Reach for a line chart when something moves over a continuous axis, like sales rising month after month.

plt.plot(months, sales)

Bars Compare Categories

Use a bar chart to compare separate groups side by side, like total sales for each region.

plt.bar(regions, totals)

Plot Straight From pandas

Every Series and DataFrame has a built-in .plot that calls matplotlib for you, so you skip the manual setup.

df["sales"].plot()

Choose the Kind

The pandas plot takes a kind argument. Pass kind="bar" for bars or leave it off for the default line.

df["sales"].plot(kind="bar")

Group Then Plot

A grouped summary plots beautifully because its index becomes the x-axis. Group, aggregate, then chain .plot.

df.groupby("region")["sales"].sum().plot(kind="bar")

Show the Figure

Outside a notebook you must call plt.show to pop the window. In Jupyter the chart appears on its own.

plt.show()

Size It Up

Tiny charts hide detail. Pass figsize as a width and height in inches to give your plot room to breathe.

df["sales"].plot(figsize=(8, 4))

Layer More Lines

Call plt.plot several times before showing and matplotlib stacks each line onto the same axes for easy comparison.

Clear Before You Redraw

Leftover plots can pile up across cells. Start fresh with plt.figure or close old ones so charts do not overlap.

Quick Check

You want to compare total sales across a few regions. Which chart fits best?

Recap: Your First Charts

You can now import plt, draw lines for trends and bars for categories, and plot straight from pandas. Your data has a face now! 🎨

常见问题解答

「matplotlib 中的折线图和条形图」课时是免费的吗？

是的 — 「matplotlib 中的折线图和条形图」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。

「matplotlib 中的折线图和条形图」这节课中我会学到什么？

直接从 DataFrame 绘图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 3 节课，共 4 节。

「matplotlib 中的折线图和条形图」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。

此课程中的所有课时

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