### Introduction

*Matplotlib* is one of the most widely used data visualization libraries in Python. Much of Matplotlib's popularity comes from its customization options - you can tweak just about any element from its *hierarchy of objects*.

In this tutorial, we'll take a look at *how to set the axis range (xlim, ylim) in Matplotlib*, to truncate or expand the view to specific limits.

### Creating a Plot

Let's first create a simple plot:

```
import matplotlib.pyplot as plt
import numpy as np
fig, ax = plt.subplots(figsize=(12, 6))
x = np.arange(0, 10, 0.1)
y = np.sin(x)
z = np.cos(x)
ax.plot(y, color='blue', label='Sine wave')
ax.plot(z, color='black', label='Cosine wave')
plt.show()
```

Here, we've plotted two sine functions, starting at `0`

and ending at `100`

with a step of `0.1`

. Running this code yields:

Now, we can tweak the range of this axis, which currently goes from `0`

to `100`

.

### Setting Axis Range in Matplotlib

Now, if we'd like to truncate that view, into a smaller one or even a larger one, we can tweak the X and Y limits. These can be accessed either through the PyPlot instance, or the `Axes`

instance.

#### How to Set X-Limit (xlim) in Matplotlib

Let's first set the X-limit, using both the PyPlot and `Axes`

instances. Both of these methods accept a tuple - the left and right limits. So, for example, if we wanted to truncate the view to only show the data in the range of 25-50 on the X-axis, we'd use `xlim([25, 50])`

:

```
fig, ax = plt.subplots(figsize=(12, 6))
x = np.arange(0, 10, 0.1)
y = np.sin(x)
z = np.cos(x)
ax.plot(y, color='blue', label='Sine wave')
ax.plot(z, color='black', label='Cosine wave')
plt.xlim([25, 50])
plt.show()
```

This limits the view on the X-axis to the data between `25`

and `50`

and results in:

This same effect can be achieved by setting these via the `ax`

object. This way, if we have multiple `Axes`

, we can set the limit for them separately:

```
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure(figsize=(12, 6))
x = np.arange(0, 10, 0.1)
y = np.sin(x)
z = np.cos(x)
ax = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
ax.set_title('Full view')
ax.plot(y, color='blue', label='Sine wave')
ax.plot(z, color='black', label='Cosine wave')
ax2.set_title('Truncated view')
ax2.plot(y, color='blue', label='Sine wave')
ax2.plot(z, color='black', label='Cosine wave')
ax2.set_xlim([25, 50])
plt.show()
```

#### How to Set Y-Limit (ylim) in Matplotlib

Now, let's set the Y-limit. This can be achieved with the same two approaches:

```
ax.plot(y, color='blue', label='Sine wave')
ax.plot(z, color='black', label='Cosine wave')
plt.ylim([-1, 0])
```

Or:

```
ax.plot(y, color='blue', label='Sine wave')
ax.plot(z, color='black', label='Cosine wave')
ax.set_ylim([-1, 0])
```

Both of which result in:

### Conclusion

In this tutorial, we've gone over *how to set the axis range (i.e. the X and Y limits) using Matplotlib in Python*.

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