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']]

Divakar · Accepted Answer · 2016-10-28 13:09:33Z

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']

edited Oct 28, 2016 at 13:09

answered Oct 28, 2016 at 13:05

Divakar

222k19 gold badges273 silver badges374 bronze badges

Sign up to request clarification or add additional context in comments.

4 Comments

elfving Over a year ago

Thank you! @Divakar

elfving Over a year ago

How would I write it if I want a result based on two values? For exampel 'jeep' and 'USA'

Divakar Over a year ago

@elfving Use np.in1d.

Divakar Over a year ago

@elfving Also have a look at this Q&A to get those indices and then simply index into the list with those indices.

Collectives™ on Stack Overflow

Numpy, new array based on an array within an array

1 Answer 1

4 Comments

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

4 Comments

Linked

Related