NumPy is an open-source Python library used for scientific computing and data analysis. It provides powerful and efficient tools for manipulating and analyzing numerical data. It is most commonly used for its array objects and functions, which are used to create and manipulate arrays of any size and shape. NumPy also provides a wide range of linear algebra functions, statistical functions, and random number generators.
The NumPy library contains a multi-dimensional array object called ndarray. It provides a collection of mathematical functions for manipulating these arrays and performing various operations on them such as sorting, indexing, reshaping, and more. NumPy is used in a wide range of applications including scientific computing and data analysis
Why Should we use NumPy arrays in place of Python list?
Numpy arrays are faster, more efficient, and more convenient for performing mathematical operations than Python lists. These are optimized for numerical operations and have a regular structure, so they consume less memory and are more efficient for mathematical operations than Python lists.
Moreover, Numpy arrays offer a wide range of built-in functions that are useful for performing mathematical operations. Besides, Numpy arrays allow for vectorized operations, meaning that you can perform operations on entire arrays at once. This is much faster than looping over elements in a Python list and performing operations on each element one at a time.
Coding Steps to do Mathematical Calculations with NumPy Arrays
Step 1. Import NumPy library with as a name “np”
Step 2. Create a NumPy array for sample data.
A. One Dimensional Array
B. Two Dimension Array
C. Three Dimension Array
Step 3. Now, reshape the dimensions of the array with the np.reshape function.
Output:-
Step 4. Now, do the mathematical operations with numpy arrays.
A. Multiplication:
B. Addition
Step 5. Convert any data type into an array.
Step 6. Do basic indexing and slicing.
Conclusion:
In conclusion, Numpy is an incredibly powerful tool for performing mathematical calculations. It allows you to work with large datasets and perform advanced calculations with ease. It is also used to construct powerful machine-learning models and is an essential tool for data scientists. With its versatile and powerful features, Numpy is a must for any data scientist looking to perform complex mathematics with ease. Check out more such blogs, visit – Learning Bix
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