Explore and practice the different types of plots that are instrumental in visualizing your data.

Python Data Analysis and Visualization

Visualization using Matplotlib for Python

Let’s draw our first figure by following a step-by-step process. This process will teach us how to draw a figure using the formal method. In this figure, we will draw two lines. Each will be generated from a defined number, obtained by using `numpy`.

# Step 1 - Create a dataset
We will start by creating our dataset, which will consist of two lines. In this example, we will use `numpy` to generate a series of points on the x-axis. Then, we will use `sin` to generate a corresponding series of points on the y-axis.

```
import numpy as np

points = np.linspace(-5, 5, 256)
y1 = np.power(points, 3) + 2.0
y2 = np.sin(points) - 1.0
```

# Step 2 - Create a canvas
We will then create a canvas with only one axis. The function `subplots()` helps us create a figure, or canvas, with a specified layout. If we don’t pass the `nrows` or `ncols` parameters, `subplots()` will create a canvas with only one axes.

```
import matplotlib.pyplot as plt
fig, axe = plt.subplots()
```

# Step 3 - Add data to the axes
Next, we will add data to the axes by using `plot`. By default, the first argument is for the x-axis, and the second argument is for the y-axis.

```
axe.plot(points, y1)
axe.plot(points, y2)
```

# Step 4 - Show the figure
We can show our figure by calling `plt.show()`.

>Notice: The `plt` here is a reference to `matplotlib.pyplot`.

```
plt.show()
```

>**NOTICE**: The code above is different from the code below. On a PC, we can call `plt.show()` to display an image on the screen. However, in the example code below, we need to output the image as a file.

In this lesson, we will learn how to draw a line on a canvas by using the function subplot().

How to Draw a Figure