NumPy - with I/O. The ndarray objects can be saved to and loaded from the disk files. The IO functions available are − load() and save() functions handle /numPy binary files (with npy extension)loadtxt() and savetxt() functions handle…
In this chapter, we will discuss about NumPy - Histogram Using Matplotlib. This numPy has a numpy.histogram() function that is a graphical representation of the frequency distribution of data. Rectangles of equal…
In this chapter, we will discuss about NumPy - Matplotlib. This matplotlib is a plotting library for Python. It is used along with NumPy to provide an environment that is…
In this chapter, we will discuss about NumPy-linalg inverse. We use numpy.linalg.inv() function to calculate the inverse of a matrix. The inverse of a matrix is such that if it is multiplied…
In this chapter, we will discuss about NumPy-linalg solve. The numpy.linalg.solve() function gives the solution of linear equations in the matrix form. Considering the following linear equations − x + y +…
In this chapter, we will discuss about NumPy - Determinant. The determinant is a very useful value in linear algebra. It is calculated from the diagonal elements of a square…
In this chapter, we will discuss about NumPy-matmul. The numpy.matmul() function returns the matrix product of two arrays. While it returns a normal product for 2-D arrays, if dimensions of either argument…
In this chapter, we will discuss about NumPy-inner. This function returns the inner product of vectors for 1-D arrays. For higher dimensions, it returns the sum-product over the last axes.…
In this chapter, we will discuss about NumPy-vdot. This function returns the dot product of the two vectors. If the first argument is complex, then its conjugate is used for…
In this chapter, we will discuss about NumPy-dot. This function returns the dot product of two arrays. For 2-D vectors, it is the equivalent to matrix multiplication. For 1-D arrays,…