To keep it simple, we’re just naming them ‘x’, ‘y’and ‘z’ respectively. The output will look something like this: Now, to create a blank 3D axes, you just need to add “projection=’3d’ ” to plt.axes() axes = plt.axes(projection='3d') Let’s first start by defining our figure fig=plt.figure() Now, let’s see what our values are : print(x)Īrray() Plotting our 3d graph in Python with matplotlib We then define our numpy arrays by using the randint() function and list comprehension. Here, we’ll create three numpy arrays representing x, y, and z values.įor this, first import numpy and randint() function to create random datavalues: import numpy as np

You can also make use of a csv or excel dataset to make it easier to visualize. Now we need to get our x, y, and z values so that we can plot them. We will also import matplotlib.pyplot itself too. The submodule of matplotlib called mpl_toolkits is used to plot our 3D graphs. There are also other options like pandas3D. In this tutorial, we will be using the 3D plots in matplotlib. So, you need to make sure you have installed matplotlib to implement this tutorial. The submodule we’ll be using for plotting 3D-graphs in python is mplot3d which is already installed when you install matplotlib. 3D graphs represent 2D inputs and 1D output. Matplotlib is an amazing module which not only helps us visualize data in 2 dimensions but also in 3 dimensions. Today we’ll learn about plotting 3D-graphs in Python using matplotlib.

Python graphing code