Название: A Hands-On Introduction to Essential Python Libraries and Frameworks (With Code Samples)Автор: Murat Durmus
Издательство: Independently published
Год: 2023
Страниц: 170
Язык: английский
Формат: pdf (true), azw3, epub, mobi
Размер: 10.2 MB
Essential Python libraries and frameworks that every aspiring data scientist, ML engineer, and Python developer should know.
Python is a popular high-level programming language for various applications, including web development, scientific computing, data analysis, and machine learning. Its simplicity, readability, and versatility have made it a popular choice for programmers of all levels of expertise.
Data Science is an interdisciplinary field that involves extracting, analyzing, and interpreting large, complex data sets. It combines elements of statistics, computer science, and domain expertise to extract insights and knowledge from data. Data scientists use various tools and techniques to collect, process, and analyze data, including statistical analysis, Machine Learning, data mining, and data visualization. They work with large, complex data sets to uncover patterns, relationships, and insights that can inform decision-making and drive business value.
Python Pandas is an open-source data manipulation and analysis library for the Python programming language. It provides a set of data structures for efficiently storing and manipulating large data sets, as well as a variety of tools for data analysis, cleaning, and preprocessing. Some of the key data structures in Pandas include the Series, which is a one-dimensional array-like object that can hold any data type; and the DataFrame, which is a two-dimensional tabular data structure with rows and columns that can be thought of as a spreadsheet or a SQL table.
NumPy is a Python library for numerical computing. It provides powerful data structures, such as n-dimensional arrays or "ndarrays", and a wide range of mathematical functions for working with these arrays efficiently. It is widely used in Data Science, Machine Learning, scientific computing, and engineering, among other fields. It is built on top of low-level languages like C and Fortran, which allows NumPy to be fast and efficient even when working with large datasets.
Seaborn is a Python data visualization library built on top of Matplotlib. It provides a high-level interface for creating informative and attractive statistical graphics in Python. Seaborn is designed to work seamlessly with Pandas, a popular data manipulation library in Python, and it can handle large and complex datasets with ease. It also provides a range of customization options for plots, including color palettes, themes, and styling. Overall, Seaborn is a powerful and user-friendly library for creating informative and visually appealing statistical graphics in Python.
Scipy is an open-source scientific computing library for Python that provides a collection of functions for mathematics, science, and engineering. It is built on top of the NumPy library, which provides efficient array operations for numerical computing.
Matplotlib is a popular data visualization library for the Python programming language. It provides a way to create a wide range of static, animated, and interactive visualizations in Python. Matplotlib is designed to work well with NumPy, a popular numerical computing library for Python, and is often used in conjunction with other scientific computing libraries such as SciPy and Pandas.
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