Numpy and Pandas Essentials: Data Made Simple
Greetings to all data science enthusiasts, As mentioned in my previous posts, I will share the most important parts of what we learned in each week of my bootcamp. In this post, I will write about the second week. The most important parts of the second week were generally the Numpy and Pandas training. Let me start by talking about Numpy first.
Numpy
Numpy is the abbreviation for Numerical Python. It is a library that is developed for mathematics and statistics operations. Unlike lists, numpy holds data with a fixed type, allowing for efficient operations. It provides the capability to perform more operations with less effort. There are two main reasons for using Numpy. The first is definitely Speed. It operates very quickly because single data type. It saves a lot of time when dealing with large datasets. The second reason is that it easily enables high-level operations. Numpy offers effective capabilities to work with multi-dimensional arrays and matrices. This makes it ideal for scientific and mathematical calculations such as linear algebra, matrix operations, and statistical operations. Additionally, these multi-dimensional arrays allow for more efficient organization and processing of data. Numpy provides a wide range of mathematical functions for mathematical operations. These functions include trigonometric functions, linear…
