Adding and removing data

Introduzione a NumPy

Izzy Weber

Core Curriculum Manager, DataCamp

Concatenating in NumPy

Two arrays being added together to form one array with elements of both

Concatenating rows

classroom_ids_and_sizes = np.array([[1, 22], [2, 21], [3, 27], [4, 26]])
new_classrooms = np.array([[5, 30], [5, 17]])

np.concatenate((classroom_ids_and_sizes, new_classrooms))

array([[ 1, 22],
       [ 2, 21],
       [ 3, 27],
       [ 4, 26],
       [ 5, 30],
       [ 5, 17]])

np.concatenate() concatenates along the first axis by default.

Concatenating columns

classroom_ids_and_sizes = np.array([[1, 22], [2, 21], [3, 27], [4, 26]])
grade_levels_and_teachers = np.array([[1, "James"], [1, "George"], [3,"Amy"],
                                      [3, "Meehir"]])
np.concatenate((classroom_ids_and_sizes, grade_levels_and_teachers), axis=1)

array([['1', '22', '1', 'James'],
       ['2', '21', '1', 'George'],
       ['3', '27', '3', 'Amy'],
       ['4', '26', '3', 'Meehir']])

Shape compatibility

A three by three array and a four by two array which throw a value error when concatenated due to shape incompatibility

Two arrays being added together to form one array with elements of both

Dimension compatibility

A three by three array and a 1D array of three elements which are not compatible dimension and throw a value error

A three by three array and a three by one array which are compatible in both shape and dimension

Creating compatibility

array_1D = np.array([1, 2, 3])
column_array_2D = array_1D.reshape((3, 1))
column_array_2D

array([[1],
       [2],
       [3]])

row_array_2D = array_1D.reshape((1, 3))
row_array_2D

array([[1, 2, 3]])

Concatenating new dimensions

Graphic of two 2D arrays being stacked on top of each other to create a 3D array

Graphic which calls out this operation cannot be done with np.concatenate()

Deleting with np.delete()

classroom_data

array([['1', '22', '1', 'James'],
       ['2', '21', '1', 'George'],
       ['3', '27', '3', 'Amy'],
       ['4', '26', '3', 'Meehir']],)

np.delete(classroom_data, 1, axis=0)

array([['1', '22', '1', 'James'],
       ['3', '27', '3', 'Amy'],
       ['4', '26', '3', 'Meehir']])

Deleting columns

np.delete(classroom_data, 1, axis=1)

array([['1', '1', 'James'],
       ['2', '1', 'George'],
       ['3', '3', 'Amy'],
       ['4', '3', 'Meehir']]')

Deleting without an axis

classroom_data

array([['1', '22', '1', 'James'],
       ['2', '21', '1', 'George'],
       ['3', '27', '3', 'Amy'],
       ['4', '26', '3', 'Meehir']],)

np.delete(classroom_data, 1)

array(['1', '1', 'James', '2', '21', '1', 'George', '3', '27', '3', 'Amy',
       '4', '26', '3', 'Meehir'])

Let's practice!

Introduzione a NumPy