# Plotting A 2D Heatmap Using Matplotlib In Python

## Illustration

This tutorial is based on plotting a 2-D heatmap using matplotlib in Python programming. A heatmap can be plotted using various methods, but here in this tutorial, we are going to focus on constructing a heatmap using matplotlib.

## Heatmap

A heatmap is a data visualization technique. A heatmap looks at the correlation values and converts them into colors in 2-dimensions. It interprets numbers very simply, it is used to simplify matrices of extremely higher order to find the relationship between vast numbers of variables in a matrix graphically.

## Matplotlib

Matplotlib is a library in Python which is extremely useful in plotting various numbers of graphical plots for creating a relationship between various data structures.

### Method to import matplotlib into the code space

```import matplotlib.pyplot as plt
# or
from matplotlib import pyplot as plt```

## Algorithm

`Step 1:`

The first step is importing the matplotlib library to the code space as mentioned above.

`Step 2:`

The second step is importing the NumPy library to the code space as mentioned below.

`import numpy as np`

The need for the NumPy library is to fetch data in the form of an array with a particular shape but arbitrary values, so that a heatmap is created for this data. An example of such data structure is given below:

```import numpy as np
value=np.random.rand(5,5)
value```

output:

`Step 3:`

We use `plt.imshow()` method to plot the heatmap.

```plt.imshow(value,cmap='magma')
# Here 'magma' is one of the styles of colormap in matplotlib.```
`Step 4:`

The final step is to view the heatmap in the output section using the `plt.show()` method.

`plt.show()`

## The complete code for reference is mentioned below

```from matplotlib import pyplot as plt
import numpy as np
value=np.random.rand(5,5)
plt.imshow(value,cmap='magma')
plt.title("Heatmap")
plt.show()```

Output: