Numpy, new array based on an array within an array

Question

I'm looping over an array to extract data but it's too slow. Is there a function in numpy that will do this faster? I have to create a new array based on values from an array within an array.

For example, create an array with cars made in USA.

 input: array = [['ford', 'USA'], ['volkswagen', 'Germany'], ['jeep', 'USA']]
 output: new_array = [['ford', 'USA'], ['jeep', 'USA']]

Answer 1

Assuming an array of string dtype, you can slice out the second column and compare against the string 'USA' to get a boolean array. This boolean array could then be used for indexing into the array using boolean-indexing to select valid rows and give us the desired output.

Thus, the implementation would be simply -

array[array[:,1] == 'USA']

• elfving: Thank you! @Divakar
• elfving: How would I write it if I want a result based on two values? For exampel 'jeep' and 'USA'
• Divakar: @elfving Use np.in1d.
• Divakar: @elfving Also have a look at this Q&A to get those indices and then simply index into the list with those indices.