2 years ago

# 5 Numpy functions you didn't know you needed in scientific computation

NumPy is the fundamental package for scientific computing in Python. It is a 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.

### 5 useful Numpy Functions

1. `np.char.add()` This function concatenates element-wise the strings of two arrays of matrices.
1. `np.linalg.det()` This function is used to calculate the determinant of a square matrix
1. `np.trim_zeros()` This function will trim the leading and trailing zeros
1. `np.sort()` This function is used to sort the values in an array
1. `np.unique()` This function help us to find the unquie values in an array
``!pip install jovian --upgrade -q``
``import jovian``
``````jovian.commit(project='numpy-array-operations')
``````
```[jovian] Updating notebook "anilpiparaiya/numpy-array-operations" on https://jovian.ai [jovian] Committed successfully! https://jovian.ai/anilpiparaiya/numpy-array-operations ```
``'https://jovian.ai/anilpiparaiya/numpy-array-operations'``

Let's begin by importing Numpy and listing out the functions covered in this notebook.