Data enumerator lib

This library helps to manipulate the 2d arrays. User can execute functions like addition, substraction, multipliaction and other operations on square matrix and determinant. It also helps user to get equation of graph using arrays, which helps to predict the next value.

Functionality:-

• Used to collect user data and process it according to user requirements.
• Can be used in create recommendation system.
• Used in deep learning model training.
• Used in unsupervised machine learning projects.
• Used in predicting data

Installation

• Run the following command

git clone https://github.com/abhineetraj1/dataEnumerator
cd dataEnumerator

• Save the test file in this folder in order to import class and functions from enumerator

Docs :-

To add two matrix

from enumerator import matrix

A=[[1,2],
  [3,4]]
B=[[9,2],
  [3,8]]

C = matrix.add(A,B)

print(C)

Output :-

[[10,4],
[6,12]]

To substract two matrix

from enumerator import matrix

A=[[1,18],
  [3,14]]
B=[[9,2],
  [3,8]]

C = matrix.substract(A,B)

print(C)

Output :-

[[-8,16],
[0,6]]

To multiply two matrix

from enumerator import matrix

A=[[1,2],
  [3,4]]
B=[[0,1],
  [1,0]]

C = matrix.multiply(A,B)

print(C)

Output :-

[[1,2],
[3,4]]

To get transpose of matrix

from enumerator import matrix

A=[[1,2],
  [3,4]]

C = matrix.transpose(A)

print(C)

Output :-

[[1,3],
[2,4]]

To substract particular number with all the elements of determinant

from enumerator import determinant
A = [[2,4],
  [6,7]]

B = determinant.substractNum(2)
print(B)

Output :-

[[0,2],
[4,5]]

To add particular number with all the elements of determinant

from enumerator import determinant
A = [[2,4],
  [6,7]]

B = determinant.addNum(1)
print(B)

Output :-

[[3,5],
[7,8]]

To divide particular number with all the elements of determinant

from enumerator import determinant
A = [[3,9],
  [6,12]]

B = determinant.divideNum(2)
print(B)

Output :-

[[1,3],
[2,4]]

To multiply particular number with all the elements of determinant

from enumerator import determinant
A = [[2,4],
  [6,7]]

B = determinant.substractNum(5)
print(B)

Output :-

[[10,20],
[30,35]]

Graphical equation handling

x_data = [1, 2, 3, 4, 5]
y_data = [2, 4, 6, 8, 10]

graph_fitter = graphEQ(x_data, y_data)

graph_fitter.fit_linear()
print(graph_fitter.get_equation())  # Output: y = 2.00x

graph_fitter.fit_polynomial(2)
print(graph_fitter.get_equation())  # Output: y = 0.00x^2 + 2.00x

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Developer

• abhineetraj1