Introduction
Python provides a function called “polyfit()”, which can be imported from the module “Numpy”, which is used to fit the data within a polynomial function. There are different parameters, such as representing x-coordinate, y-coordinate values, polynomial degrees, etc.
In the article “Numpy polyfit() Method in NumPy”, we will discuss what is Numpy library, the polyfit() method in Numpy, and the implementation of the polyfit() method in Numpy.
Numpy Library
In the article “Numpy polyfit() Method in NumPy”, we will discuss the Numpy Library. Numpy stands for “Numerical Python” and is a library provided by Python which is basically used for working with arrays that functions which is be useful in the domain of linear algebra, matrices, and fourier transform.
Two of the major reasons for using the Numpy library are faster execution time, and it can also be used with various libraries such as Pandas, Scipy, and Scikit-learn. There can be different applications where the Numpy library can be used in Machine Learning, Data Science, Scientific Computing, and Quantum Computing.
Importing Numpy Library
Here is the syntax below by which the Numpy library can be imported:
import numpy as np
Implementation of Numpy Library
In this subsection of article “Numpy polyfit() Method in NumPy”, we will discuss some examples by which we can learn how to implement Numpy arrays and its operations.
Numpy Array Creation
In this example, we will create Numpy array using Numpy library:
- Python
Python
import numpy as np
# create numpy array
arr = np.array([2, 9, 10, 30])
# Output: [2 9 10 30]
print(arr)
Output
Explanation
In the above code, the First numpy library is imported as np. Now array() function is used from the library Numpy where the list is passed of 4 elements. Lastly, this created Numpy array is printed.
Numpy Array Arithmetic Operation
In this example, we will subtract one Numpy array from the Numpy array using subtract() method of the library Numpy:
- Python
Python
# importing library numpy
import numpy as np
# creating two Numpy arrays for arithmetic operation
arr1 = np.array([2, 4, 6, 8])
arr2 = np.array([1, 3, 5, 7])
# using "-" operator for subtracting arr1 with arr2
res1 = arr1 - arr2
print("Using the - operator:", res1)
# using "subtract()" function for subtracting arr1 with arr2
res2 = np.subtract(arr1, arr2)
print("Using the subtract() function in Numpy:", res2)
Output
Explanation
In the above code, the First numpy library is imported as np. Now array() function is used from the library Numpy where 2 lists are created. Now “-” operator is used, and subtract() method of Numpy is used to subtract these lists. Lastly, this created Numpy array is printed.
Numpy Array Comparison Operation
In this example, we will compare every element of 2 Numpy arrays where the greater_equal() method of the library Numpy:
- Python
Python
# importing library numpy
import numpy as np
# creating two Numpy arrays for comparison operation
arr1 = np.array([9, 12, 21])
arr2 = np.array([21, 12, 9])
# use of greater_equal() for comparing two Numpy arrays
res = np.greater_equal(arr1, arr2)
print("Using greater_equal():", res)
Output
Explanation
In the above code, the First numpy library is imported as np. Now array() function is used from the library Numpy where 2 lists are created. Now the “greater_equal()” method of Numpy is used to compare the elements of these lists. Lastly, this created Numpy array is printed.
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