Search

Introduction to Python Matplotlib Subplots

## In This Article, You Will Learn About Python Matplotlib Subplots.

Python Matplotlib Subplots – Before moving ahead, let’s take a look at Python Matplotlib Grid Lines

### The subplots() Function

The subplots() function takes three arguments to describe how the figure is laid out.

The layout is divided into rows and columns, shown in two arguments: the first and second argument.

The third argument is what is known as the index on the plot currently in use.

### Display Multiple Plots

To multiple plots in a single graph, we can use subplot() function.

Example: Adding subplots to graph.

```				```
import matplotlib.pyplot as plt
import numpy as np

#plot 1
x_axis = np.array([10, 18, 25, 36, 48])
y_axis = np.array([20, 26, 17, 31, 29])
plt.subplot(1, 2, 1)
plt.plot(x_axis, y_axis)

#plot 2
x_axis = np.array([20, 28, 15, 26, 38])
y_axis = np.array([19, 26, 37, 21, 19])

plt.subplot(1, 2, 2)
plt.plot(x_axis, y_axis)

plt.show()

```
```

As shown above, it returned a plot that has two graphs.

Now, if we want a figure with 3 rows a 1 column, we can write the syntax like this –

Example: Adding three subplots to graph.

```				```
import matplotlib.pyplot as plt
import numpy as np

#plot 1
x_axis = np.array([10, 18, 25, 36, 48])
y_axis = np.array([20, 26, 17, 31, 29])
plt.subplot(3, 1, 1)
plt.plot(x_axis, y_axis)

#plot 2
x_axis = np.array([20, 28, 15, 26, 38])
y_axis = np.array([19, 26, 37, 21, 19])
plt.subplot(3, 1, 2)
plt.plot(x_axis, y_axis)

#plot 3
x_axis = np.array([20, 28, 15, 26, 38])
y_axis = np.array([19, 26, 37, 21, 19])
plt.subplot(3, 1, 3)
plt.plot(x_axis, y_axis)

plt.show()

```
```

As shown above, it returned a plot that has three graphs.

You can draw as many plots as you like on one figure; describe the number of rows, columns, and plot index.

Example: Adding four subplots to graph.

```				```
import matplotlib.pyplot as plt
import numpy as np

#plot 1
x_axis = np.array([10, 18, 25, 36, 48])
y_axis = np.array([20, 26, 17, 31, 29])
plt.subplot(2, 2, 1)
plt.plot(x_axis, y_axis)

#plot 2
x_axis = np.array([20, 28, 10, 26, 38])
y_axis = np.array([9, 16, 27, 22, 19])
plt.subplot(2, 2, 2)
plt.plot(x_axis, y_axis)

#plot 3
x_axis = np.array([20, 17, 21, 26, 32])
y_axis = np.array([15, 21, 24, 23, 18])
plt.subplot(2, 2, 3)
plt.plot(x_axis, y_axis)

#plot 4
x_axis = np.array([10, 20, 15, 26, 38])
y_axis = np.array([14, 26, 17, 10, 19])
plt.subplot(2, 2, 4)
plt.plot(x_axis, y_axis)

plt.show()

```
```

As shown above, it returned a plot that has four graphs.

### Title

To add title in graph, we can use title() function.

Example: Adding title name to graphs.

```				```
import matplotlib.pyplot as plt
import numpy as np

#plot 1
x_axis = np.array([10, 18, 25, 36, 48])
y_axis = np.array([20, 26, 17, 31, 29])
plt.subplot(2, 1, 1)
plt.plot(x_axis, y_axis)
plt.title("Record-x")

#plot 2
x_axis = np.array([20, 28, 15, 26, 38])
y_axis = np.array([19, 26, 37, 21, 19])
plt.subplot(2, 1, 2)
plt.plot(x_axis, y_axis)
plt.title("Record-y")

plt.show()

```
```

As a result, it returned a graph after adding title for each graph.

### Super Title

To add a title name to entire graph, we can use supertitle() function.

Example: Adding a title name to entire graph.

```				```
import matplotlib.pyplot as plt
import numpy as np

#plot 1
x_axis = np.array([10, 18, 25, 36, 48])
y_axis = np.array([20, 26, 17, 31, 29])
plt.subplot(2, 1, 1)
plt.plot(x_axis, y_axis)
plt.title("Record-x")

#plot 2
x_axis = np.array([20, 28, 15, 26, 38])
y_axis = np.array([19, 26, 37, 21, 19])
plt.subplot(2, 1, 2)
plt.plot(x_axis, y_axis)
plt.title("Record-y")

plt.suptitle("FY-2020")

plt.show()

```
```

As shown above, it returned a graph after adding title name as entire name of the graph.

If you find anything incorrect in the above-discussed topic and have any further questions, please comment below.

Connect on:

Share on