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# Adding Titles, Labels, and Legends

 

Once you’ve customized the style of your plot, the next step is to clearly label it. Labels tell viewers **what the data means** and make the chart easier to understand.

In this lesson, you’ll learn how to add a **title**, axis **labels**, and a **legend** to explain different data series.

 

## Title

Use `plt.title()` to add a heading to your chart.

```python title="Adding a Plot Title"
plt.title("Monthly Revenue")
```

 

## Axis Labels

Use `plt.xlabel()` and `plt.ylabel()` to label the x-axis and y-axis.

```python title="Adding Axis Labels"
plt.xlabel("Month")
plt.ylabel("Revenue ($)")
```

These labels help the reader understand what the axes represent.

 

## Legends

If you plot more than one line, use `label=` inside `plt.plot()` and call `plt.legend()` to display a legend.

```python title="Adding a Legend to Multiple Lines"
plt.plot(x, y1, label="Product A")
plt.plot(x, y2, label="Product B")
plt.legend()
```

The legend will show which line corresponds to which label.

 

## What’s Next?

Now that your plots are fully labeled and explained, we’ll explore **bar and pie charts** to visualize data that isn’t best shown as a line.

In Matplotlib, when you have multiple lines in a plot, adding a legend allows viewers to distinguish between the different data series. Use `plt.legend()` after defining labels within `plt.plot()`, thus making your chart more informative and easier to interpret.

### How can you add a legend to a Matplotlib plot with multiple lines?