Array Transposition – Numpy Python Data Analysis
Welcome Guys, We will be looking at Array transposition in this quick notes. This is part of lectures on Learning Python for Data Analysis and Visualization by Jose Portilla on Udemy. In [1]:
|
1 |
import numpy as np |
In [2]:
|
1 2 |
arr = np.arange(50) arr |
Out[2]:
|
1 2 3 |
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]) |
In [17]:
|
1 |
arr.reshape((10,5)) |
Out[17]:
|
1 2 3 4 5 6 7 8 9 10 |
array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24], [25, 26, 27, 28, 29], [30, 31, 32, 33, 34], [35, 36, 37, 38, 39], [40, 41, 42, 43, 44], [45, 46, 47, 48, 49]]) |
In [10]:
|
1 |
arr.T |
Out[10]:
|
1 2 3 |
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]) |
In [11]:
|
1 |
np.dot(arr.T, arr) |
Out[11]:
|
1 |
40425 |
In [23]:
|
1 |
arr3d = np.arange(50).reshape((5,5,12)) |
|
1 2 3 4 5 6 |
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-23-8908d625ec66> in <module>() ----> 1 arr3d = np.arange(50).reshape((5,5,12)) ValueError: total size of new array must be unchanged |
…