**Data visualization** is a significant aspect of data science. It is used to present data in a sensible manner for statistical or comparative analysis. 

**`matplotlib`** is a Python library that provides a multitude of functions to visualize and plot data. 

The **`matplotlib.pyplot.plot()`** function is used to plot two scalar values against each other as lines or markers.

#     
## Syntax

```py
plot([x], y, [fmt], *, data=None, **kwargs)
```

## Parameters
-  **`x`**,**`y`**: Can be arrays or scalars. They correspond to the x-axis and y-axis values. The x-axis values are optional and the default value of `x` is `range(len(y))`.

- **`fmt`**: A string value that specifies the formatting of the lines. (Optional)
- **`data`**: A object that contains labeled data. (Optional)

## Return value
`matplotlib.pyplot.plot()` returns a list of `Line2D` objects that represent the data.

## Code
The code below plots a line that joins multiple points.

#import libraries
import matplotlib.pyplot as plt
import numpy as np

#initialize x-axis and y-axis values
x = np.array([1, 2, 3, 4])
y = np.array([1, 4, 9, 16])

#plot a line
plt.plot(x, y)
plt.show()

To plot points without a line, the relevant format string is passed as parameter. 

#import libraries
import matplotlib.pyplot as plt
import numpy as np

#initialize y-axis values with default x-axis values
y = np.array([5, 10, 7, 3])

#plot points only
plt.plot(x, y, 'o')
plt.show()

What is matplotlib.pyplot.plot() in Python?

matplotlib.pyplot.plot() visualizes data by plotting scalar values as lines or markers, offering versatile formatting options.