Adding and removing data

Introduction to 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!

Introduction to NumPy