Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|

matplotlib 3d plot rotate | 1.37 | 0.6 | 4872 | 66 | 25 |

matplotlib | 0.96 | 0.8 | 5397 | 50 | 10 |

3d | 0.94 | 0.2 | 8594 | 22 | 2 |

plot | 0.51 | 0.8 | 4596 | 33 | 4 |

rotate | 0.11 | 0.3 | 6123 | 5 | 6 |

Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|

matplotlib 3d plot rotate | 1.82 | 0.5 | 9625 | 60 |

rotate 3d plot matplotlib jupyter | 0.29 | 0.4 | 9288 | 16 |

rotate 3d scatter plot matplotlib | 1.91 | 0.6 | 6123 | 17 |

matplotlib rotate 3d plot interactive | 1.44 | 0.8 | 1444 | 61 |

matplotlib rotate 3d plot with mouse | 0.62 | 0.2 | 860 | 83 |

rotate 3d plot matplotlib | 1.94 | 0.6 | 3909 | 6 |

jupyter 3d plot rotate | 0.1 | 1 | 7756 | 52 |

jupyter notebook 3d plot rotate | 0.92 | 0.8 | 8665 | 1 |

matplotlib interactive 3d plot jupyter | 0.67 | 0.8 | 5784 | 58 |

matplotlib 3d rotate view | 0.84 | 0.1 | 6707 | 28 |

rotate 3d graph matplotlib | 1.04 | 0.8 | 5820 | 68 |

how to rotate plot in matplotlib | 0.51 | 0.3 | 473 | 46 |

matplotlib 3d rotate animation | 1.32 | 0.9 | 2978 | 16 |

matplotlib 3d 回転 jupyter | 0.09 | 0.2 | 8757 | 67 |

interactive plot matplotlib jupyter | 1.88 | 0.2 | 5385 | 12 |

rotate 3d plot python | 1.88 | 0.5 | 7825 | 39 |

matplotlib plot in jupyter notebook | 1.14 | 0.6 | 7926 | 80 |

how to rotate image in matplotlib | 0.37 | 0.4 | 2636 | 52 |

matplotlib animation in jupyter notebook | 2 | 1 | 8024 | 26 |

how to use matplotlib in jupyter | 1.26 | 0.9 | 7159 | 54 |

rotating image in matplotlib | 1.51 | 0.1 | 2238 | 80 |

Initially, matplotlib was used to plot and visualize only 2D graphs, but we should thank the mplot3d toolkit available in the matplotlib library. We can visualize 3D plots such as 3D scatter plots, 3D line plots, Surface plots, Rotated plot angles, etc.

To plot 3-D plots in python, we need to import the mplot3d library from the standard installation of matplotlib library from python. As matplotlib is a third-party library, it doesn’t come with a standard installation of python, so you need to install matplotlib before following this article.

At the last view_init () method is used to change the view angle of the 3D plot. The view_init () method takes two parameters: the elevation angle in the z-plane and the azimuth angle in the x & y plane. And finally, called the show () method to display the 3D plot.

Now using Axes3D (figure) function from the mplot3d library we can generate a required plot directly. Pass the data to the 3D plot and configure the title and labels. Note: We must needed to add ” %matplotlib widget “, it is a Jupyter magic widget and used to tell jupyter to use interactive backend for plot.