numpy.median() Function
Srinivas Ramakrishna
The NumPy library has a numpy.median() function is used to compute the median of an array in sorted order on a specified axis and returns the median of the array…
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NumPy
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What is NumPy?
NumPy stands for Numerical Python, a fundamental package for scientific computing in Python.
NumPy is a popular Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O, discrete Fourier transforms basic linear algebra, basic statistical operations, random simulation and much more.
Benefits of using NumPy
- Performance- Python was not designed for numeric computations and there was a need for fast numeric computation. NumPy solved that problem, basically, it was created in the year 2005, and it uses an algorithm written in C language that computes 10-100 times faster performance than Python.
- Clean Code – NumPy reduces loops and iterations, hence it reduces the Cyclomatic complexity
- High-Performance N-dimensional Array object – NumPy’s main object is the homogeneous multidimensional array. We can perform all the operations on the array elements and arrays of NumPy can be single-dimensional or multi-dimensional.
Prerequisites
The developers should have a basic understanding of Programming terminologies and basic knowledge of Python would be required.
How to Check the NumPy Version
There are multiple ways to check the NumPy version; however, the easiest and PEP8 standard practice is to import numpy and use the numpy.__version__ attribute to get the exact version…
numpy.ndarray.flatten() function
The numpy.ndarray.flatten() function in the NumPy array library is used to flatten an array of elements in different orders. The flattening of a NumPy n-dimensional array in python is a procedure to return a copy of…
numpy.mean() Function
The numpy.mean() is a function in the NumPy library that is used to calculate the mean of an array of elements along with an axis. In NumPy array library or…
numpy.average() Function
The numpy.average() function computes the weighted average of elements that are specified NumPy array along the specified axis. The average in linear algebra is the proportion of the sum of…
numpy.repeat() Function
The numpy.repeat() function takes the repetitions (int) as an input argument, repeats the elements of an array, and returns the repeated array as output. The repetitions can happen row and…
numpy.transpose() Function
The numpy.transpose() function takes the array as an input, reverses its dimension, and returns the transposed array. In simple terms, the NumPy transpose swaps from rows to columns and columns…
numpy.shape() Function
The numpy.shape() function will return the shape of the given array in tuple format. The shape of the array is the elements in each dimension. Dimension is the count of…
numpy.argmax() in Python
The numpy.argmax() function returns the indices of the maximum values along an axis. In case of multiple occurrences of the maximum values, the indices corresponding to the first occurrence will be returned.…
