Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Aprenda Reshaping and Stacking | Getting into NumPy Basics
Getting into NumPy Basics

book
Reshaping and Stacking

Reshaping and stacking NumPy arrays involve modifying the shape or size of an array or amalgamating multiple arrays into a single array. NumPy offers a variety of functions for these purposes, such as:

  • reshape(): Alters an array to a new shape without changing its data;
  • resize(): Changes an array's size to a new shape, which can lead to the addition or removal of elements;
  • vstack(): Vertically stacks arrays (row-wise) to form a single array;
  • hstack(): Horizontally stacks arrays (column-wise) to create a single array;
  • concatenate(): Joins arrays along a specified axis;
  • stack(): Layers arrays along a new axis, adding a dimension.
Tarefa

Swipe to start coding

  1. Reshape the arr array to a new configuration.
  2. Resize the arr array to a new dimension, possibly adding or omitting elements.
  3. Vertically stack all the arrays to produce a unified array (in the order of creation).
  4. Horizontally stack all the arrays to form a single array (in the order of creation).

Solução

import numpy as np

# Create a NumPy array
arr = np.array([[1, 2, 3], [4, 5, 6]])
arr_1 = np.array([[7, 8, 9], [10, 11, 12]])
arr_2 = np.array([[13, 14, 15], [16, 17, 18]])

# Reshape the array to a new shape
reshaped_arr = arr.reshape(3, 2)

# Resize the array to a new shape, potentially adding or removing elements
resized_arr = np.resize(arr, (4, 3))

# Stack the arrays vertically (row-wise) to create a single array
vertical_stack = np.vstack((arr, arr_1, arr_2))

# Stack the arrays horizontally (column-wise) to create a single array
horizontal_stack = np.hstack((arr, arr_1, arr_2))

display(reshaped_arr, resized_arr, vertical_stack, horizontal_stack)

Mark tasks as Completed
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 1. Capítulo 6
AVAILABLE TO ULTIMATE ONLY
some-alt