Hướng dẫn join two array python

Joining NumPy Arrays

Joining means putting contents of two or more arrays in a single array.

Nội dung chính

• Joining NumPy Arrays
• Joining Arrays Using Stack Functions
• Stacking Along Rows
• Stacking Along Columns
• Stacking Along Height [depth]
• Test Yourself With Exercises
• How do I combine two arrays?
• How do I merge two NumPy arrays in Python?
• Can we concatenate arrays in Python?
• How do I merge a list of NumPy arrays?

In SQL we join tables based on a key, whereas in NumPy we join arrays by axes.

We pass a sequence of arrays that we want to join to the concatenate[] function, along with the axis. If axis is not explicitly passed, it is taken as 0.

Example

Join two arrays

import numpy as np

arr1 = np.array[[1, 2, 3]]

arr2 = np.array[[4, 5, 6]]

arr = np.concatenate[[arr1, arr2]]

print[arr]

Try it Yourself »

Example

Join two 2-D arrays along rows [axis=1]:

import numpy as np

arr1 = np.array[[[1, 2], [3, 4]]]

arr2 = np.array[[[5, 6], [7, 8]]]

arr = np.concatenate[[arr1, arr2], axis=1]

print[arr]

Try it Yourself »

Joining Arrays Using Stack Functions

Stacking is same as concatenation, the only difference is that stacking is done along a new axis.

We can concatenate two 1-D arrays along the second axis which would result in putting them one over the other, ie. stacking.

We pass a sequence of arrays that we want to join to the stack[] method along with the axis. If axis is not explicitly passed it is taken as 0.

Example

import numpy as np

arr1 = np.array[[1, 2, 3]]

arr2 = np.array[[4, 5, 6]]

arr = np.stack[[arr1, arr2], axis=1]

print[arr]

Try it Yourself »

Stacking Along Rows

NumPy provides a helper function: hstack[] to stack along rows.

Example

import numpy as np

arr1 = np.array[[1, 2, 3]]

arr2 = np.array[[4, 5, 6]]

arr = np.hstack[[arr1, arr2]]

print[arr]

Try it Yourself »

Stacking Along Columns

NumPy provides a helper function: vstack[]  to stack along columns.

Example

import numpy as np

arr1 = np.array[[1, 2, 3]]

arr2 = np.array[[4, 5, 6]]

arr = np.vstack[[arr1, arr2]]

print[arr]

Try it Yourself »

Stacking Along Height [depth]

NumPy provides a helper function: dstack[] to stack along height, which is the same as depth.

Example

import numpy as np

arr1 = np.array[[1, 2, 3]]

arr2 = np.array[[4, 5, 6]]

arr = np.dstack[[arr1, arr2]]

print[arr]

Try it Yourself »

Test Yourself With Exercises

Exercise:

Use a correct NumPy method to join two arrays into a single array.

arr1 = np.array[[1, 2, 3]]

arr2 = np.array[[4, 5, 6]]

arr = np.[[arr1, arr2]]

Start the Exercise

All the possible ways to join lists that I could find

import itertools

A = [1,3,5,7,9] + [2,4,6,8,10]

B = [1,3,5,7,9]
B.append[[2,4,6,8,10]]

C = [1,3,5,7,9]
C.extend[[2,4,6,8,10]]

D = list[zip[[1,3,5,7,9],[2,4,6,8,10]]]
E = [1,3,5,7,9]+[2,4,6,8,10]
F = list[set[[1,3,5,7,9] + [2,4,6,8,10]]]

G = []
for a in itertools.chain[[1,3,5,7,9], [2,4,6,8,10]]:
    G.append[a]


print["A: " + str[A]]
print["B: " + str[B]]
print["C: " + str[C]]
print["D: " + str[D]]
print["E: " + str[E]]
print["F: " + str[F]]
print["G: " + str[G]]

Output

A: [1, 3, 5, 7, 9, 2, 4, 6, 8, 10]
B: [1, 3, 5, 7, 9, [2, 4, 6, 8, 10]]
C: [1, 3, 5, 7, 9, 2, 4, 6, 8, 10]
D: [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]]
E: [1, 3, 5, 7, 9, 2, 4, 6, 8, 10]
F: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
G: [1, 3, 5, 7, 9, 2, 4, 6, 8, 10]

>>> a = np.array[[[1, 2], [3, 4]]]
>>> b = np.array[[[5, 6]]]
>>> np.concatenate[[a, b], axis=0]
array[[[1, 2],
       [3, 4],
       [5, 6]]]
>>> np.concatenate[[a, b.T], axis=1]
array[[[1, 2, 5],
       [3, 4, 6]]]
>>> np.concatenate[[a, b], axis=None]
array[[1, 2, 3, 4, 5, 6]]

>>> a = np.ma.arange[3]
>>> a[1] = np.ma.masked
>>> b = np.arange[2, 5]
>>> a
masked_array[data=[0, --, 2],
             mask=[False,  True, False],
       fill_value=999999]
>>> b
array[[2, 3, 4]]
>>> np.concatenate[[a, b]]
masked_array[data=[0, 1, 2, 2, 3, 4],
             mask=False,
       fill_value=999999]
>>> np.ma.concatenate[[a, b]]
masked_array[data=[0, --, 2, 2, 3, 4],
             mask=[False,  True, False, False, False, False],
       fill_value=999999]

How do I combine two arrays?

To merge elements from one array to another, we must first iterate[loop] through all the array elements. In the loop, we will retrieve each element from an array and insert[using the array push[] method] to another array. Now, we can call the merge[] function and pass two arrays as the arguments for merging.

How do I merge two NumPy arrays in Python?

NumPy's concatenate function can be used to concatenate two arrays either row-wise or column-wise. Concatenate function can take two or more arrays of the same shape and by default it concatenates row-wise i.e. axis=0. The resulting array after row-wise concatenation is of the shape 6 x 3, i.e. 6 rows and 3 columns.

Can we concatenate arrays in Python?

Joining Arrays Using Stack Functions We can concatenate two 1-D arrays along the second axis which would result in putting them one over the other, ie. stacking. We pass a sequence of arrays that we want to join to the stack[] method along with the axis.

How do I merge a list of NumPy arrays?

To concatenate two arrays with NumPy:.

Import numpy..

Put two arrays in a list..

Call numpy. concatenate[] on the list of arrays..