PythonProgrammingIn 30 DaysDay -10

Python
Programming
In 30 Days

Day -10

Two Dimensional List

There can be more than one additional dimension to lists in Python. Keeping in mind that a list can hold other lists, that basic principle can be applied over and over. Multi-dimensional lists are the lists within lists. Usually, a dictionary will be the better choice rather than a multi-dimensional list in Python.

Example –

a = [[2, 4, 6, 8, 10], [3, 6, 9, 12, 15], [4, 8, 12, 16, 20]]
for record in a:
print(record)


Python Numpy
Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python.
Creating a Numpy Array
Arrays in Numpy can be created by multiple ways, with various number of Ranks, defining the size of the Array. Arrays can also be created with the use of various data types such as lists, tuples, etc. The type of the resultant array is deduced from the type of the elements in the sequences.

Universal Functions

Numpy, Universal functions are objects those belongs to numpy. ufunc class. Python functions can also be created as a universal function using from pyfunc library function. Some ufuncs are called automatically when the corresponding arithmetic operator is used on arrays.


import numpy as np
number=np.array([10,24,32,2])
np.sqrt(number)

# Python program to demonstrate printing
# of complete multidimensional list row
# by row.
a = [[2, 4, 6, 8, 10], [3, 6, 9, 12, 15], [4, 8, 12, 16, 20]]
for record in a:
print(record)

# Python program to demonstrate that we
# can access multidimensional list using
# square brackets
a = [ [2, 4, 6, 8 ],
[ 1, 3, 5, 7 ],
[ 8, 6, 4, 2 ],
[ 7, 5, 3, 1 ] ]

for i in range(len(a)) :
for j in range(len(a[i])) :
print(a[i][j], end=" ")
print()


# Python program for
# Creation of Arrays
import numpy as np

# Creating a rank 1 Array
arr = np.array([1, 2, 3])
print("Array with Rank 1: \n",arr)

# Creating a rank 2 Array
arr = np.array([[1, 2, 3],
[4, 5, 6]])
print("Array with Rank 2: \n", arr)

# Creating an array from tuple
arr = np.array((1, 3, 2))
print("\nArray created using "
"passed tuple:\n", arr)