In this tutorial we will show how to you can easily plot a function with Python and specifically using the Numpy, Matplotlib and Seaborn libraries.

### Draw a continuous function graph with Python and Matplotlib

In this example we’ll going to go ahead and plot a function of two variables with Matplotlib. As an example, we’ll draw a simple line graph.

```
# import libraries
import matplotlib.pyplot as plt
import numpy as np
plt.style.use('default')
# creating the test data
x = np.linspace(10, 100,10)
y=np.power(x,3)
# rendering the chart
fig,ax= plt.subplots()
plt.style.use('ggplot')
ax.plot(x,y);
ax.set_title('My Chart')
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis');
```

#### Code Steps

- We first import the Numpy and Matplotlib libraries.
- We’ll then use numpy functions numpy.linspace and np.power to quickly generate the line plot underlying data.
- Then, we use Matplotlib library to create a figure and a single plot area (referred in Matplotlib as
**axes**), then render the graph itself using the plt.plot command. - Las we customize our chart and assign a title and labels to the x and y axes.

Note that there are hundreds of possible customization that you can apply to our chart, whcih we covered in our other visualization tutorials.

Note II: In the same fashion you can draw other defined functions either piecewise and continuous (such as sine (using np.sin() , linear and so forth).

#### Chart

### Plotting a continuous function plot with Seaborn

```
# using seaborn
import seaborn as sns
import numpy as np
# create data
x = np.linspace(10, 100,10)
y=np.power(x,3)
# draw the graph
sns.set_style('dark')
fig,ax= plt.subplots()
ax = sns.lineplot(x=x, y=y)
ax.set_title('My Chart (using Seaborn)')
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis');
```

#### Steps

The code is quite similar to the one provided above. The main difference is the usage of the Seaborn library.

- Import Seaborn and Numpy.
- Definition of the dataset and continuous function X^3.
- Rendering the graph using the Seaborn sns.lineplot method.
- Some simple customizations to the chart (title and labels).