Basic Python with Libraries – Math, Numpy, Pandas, Matplotlib, Seaborn and textblob

For those who have never used Python before, this fast start guide offers a starting point for exploring the world of machine and deep learning. It presents fundamental Python fundamentals, including mathematical operations and important data types, and is tailored for students and working professionals entering the field of machine learning. Additionally, it emphasises key libraries for data manipulation, visualisation, and natural language processing such Pandas, NumPy, Matplotlib, Seaborn, and TextBlob. People may analyse data and create prediction models by using the underlying information and code examples provided in this succinct introduction to the fascinating topics of machine learning and deep learning.

Basic Math Operations: Python can perform standard arithmetic operations, such as addition (+), subtraction (-), multiplication (*), division (/), and exponentiation (**). Additionally, the modulo operator (%) calculates remainders.

Variables: Variables store data. In Python, you can create variables without declaring their type, e.g., x = 5. Variables can hold numbers, strings, or other data types.

Data Types: Python supports various data types, including integers, floating-point numbers, strings, lists, tuples, and dictionaries.

Control Structures: Python uses conditional statements (if, elif, else) and loops (for, while) to control program flow.

Introduction to Libraries:

NumPy: NumPy is a fundamental library for numerical computations in Python. It provides multidimensional arrays (numpy arrays) and a wide range of mathematical functions for array manipulation.

Pandas: Pandas is a powerful library for data manipulation and analysis. It introduces two primary data structures, Series (1D) and DataFrame (2D), making it easy to work with structured data.

Matplotlib: Matplotlib is a popular library for creating static, animated, or interactive visualizations in Python. It offers a wide range of chart types and customization options.

Seaborn: Seaborn is built on top of Matplotlib and simplifies the creation of aesthetically pleasing statistical visualizations. It is particularly useful for exploring data distributions and relationships.

TextBlob: TextBlob is a library for processing textual data, especially for natural language processing (NLP) tasks. It simplifies tasks like sentiment analysis, part-of-speech tagging, and text classification.

These libraries are essential tools for data analysis, scientific computing, and data visualization in Python. They greatly enhance the language's capabilities and efficiency, making it a go-to choice for data scientists and analysts. Understanding these fundamentals is crucial for anyone working with data in Python.