To **plot** a **line** **plot** in **Matplotlib**, you can use the **“matplotlib.pyplot.plot()”** function. There’s no specific **lineplot()** function. Instead, line plots display numerical values on one axis and categorical values on the other.

A **line plot** is used to display the continuous values. The points are connected using the line; hence this plot is called a line plot. The line plot can be plotted using the **matplotlib.pyplot.plot()** function. The plot() function creates a graph for the given points; the displayed graph is in the form of lines.

**Syntax**

`matplotlib.pyplot.plot(*args, scalex=True, scaley=True, data=None, **kwargs)`

**Arguments**

The **matplotlib.pyplot.plot()** function has one required argument and four optional arguments as parameters:

**args – x,y**: This parameter has two values, x, and y. The points are passed in the x and y argument. This x and y can have values like numbers or a list of numbers.**fmt**: fmt stands for format. This is an optional argument. This argument takes a string as the argument. This string represents the format in which the graph is needed to be created. For example, some color codes used in string formats are r for red, b for blue, g for green, and y for yellow. Likewise, some of the markers used in the string formats are “o” for circle, ‘.’ for point, ‘*’ for star, and “+” for plus.**data**: It is an object with labeled data passed as an argument. This is an optional argument.

**Return value**

The plot() function returns a list of 2d lines representing the plotted data. The returned list consists of points on the line graph.

**Example 1**

```
# Importing matplotlib.pyplot as plt.
import matplotlib.pyplot as plt
# Importing numpy as np
import numpy as np
# create a numpy array for storing the x coordinates
x = np.arange(0, 100, 10)
# create a numpy array for storing the y coordinates
y = np.arange(0, 50, 5)
# pass the x coordinates and y coordinates into the plot() function
plt.plot(x, y)
# displaying the created graph using the show method
plt.show()
```

**Output**

In this program, we imported **matplotlib.pyplot** for plotting the line graph. The matplotlib library consists of all the functions for plotting different types of graphs. Then we imported numpy for creating x and y coordinates.

Then, we created x and y coordinates and stored the **numpy** **array** in the x and y variables.

The x variable stores the values from 0 to 100 in intervals of 10, and the y variable stores the values from 0 to 50 in an interval of 5. Then, we passed the two coordinates into the **plot()** function. The **plot()** function plots the graph across the x and y-axis.

This generated **graph** is called the **line** **graph**. The output graph is a straight line. Then, the graph is displayed using the show() function.

**Example 2**

To **plot** **multiple** **lines** in **Python**, you can use the **“matplotlib.pyplot.plot()”** function.

```
# Importing matplotlib.pyplot as plt.
import matplotlib.pyplot as plt
# Importing numpy as np
import numpy as np
# create a numpy array for storing the x coordinates
x = np.arange(0, 100, 10)
# create a numpy array for storing the y coordinates
y = np.arange(0, 50, 5)
# x and y coorindates for the second line is stored in the variable
u = np.arange(90, -10, -10)
v = np.arange(0, 50, 5)
print(u)
print(v)
# the plot function is called with coordinates x,y,u,v
plt.plot(x, y, u, v)
# displaying the created graph using the show method
plt.show()
```

**Output**

In this program, we imported **matplotlib.pyplot** for plotting the graph. The matplotlib library consists of all the functions for plotting different types of graphs. Then, we imported numpy for creating x and y coordinates.

Then, we created x and y coordinates and stored this numpy array in x and y variables. Then, we created the x and y coordinates for the second line and stored them in the u and v variables.

Then, we called the plot() function with x and y as the first argument. Then, we passed the second line coordinates. The plot() function creates two lines in a single plot. These lines intersect with each other in their center.