How to Index a 2D NumPy Array Using Two Lists of Indices?

Indexing a 2D NumPy Array with 2 Lists of Indices

Using np.ix_ with Indexing Arrays

To index a 2D NumPy array using two lists of indices, arrays,, we can use the np.ix_ function in conjunction with indexing arrays.

<code class="python">x_indexed = x[np.ix_(row_indices, col_indices)]</code>

Using np.ix_ with Masks

Alternatively, we can use np.ix_ with boolean masks to select and index the array:

<code class="python">row_mask = [0, 1, 1, 0, 0, 1, 0]
col_mask = [1, 0, 1, 0, 1, 1, 0, 0]

x_indexed = x[np.ix_(row_mask, col_mask)]</code>

Example

Consider the following example:

<code class="python">import numpy as np

x = np.random.randint(0, 6, (20, 8))

row_indices = [4, 2, 18, 16, 7, 19, 4]
col_indices = [1, 2]</code>

To index x using the provided lists, we can use either method:

<code class="python"># Using np.ix_ with indexing arrays
x_indexed = x[np.ix_(row_indices, col_indices)]

# Using np.ix_ with masks
row_mask = np.isin(np.arange(x.shape[0]), row_indices)
col_mask = np.isin(np.arange(x.shape[1]), col_indices)

x_indexed = x[np.ix_(row_mask, col_mask)]</code>

Both methods will result in the desired indexed array:

<code class="python">>>> x_indexed
array([[76, 56],
       [70, 47],
       [46, 95],
       [76, 56],
       [92, 46]])</code>

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