Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

Unlock the full potential of Python's most essential library for numerical computing, NumPy. This comprehensive course is designed to take you from a beginner's understanding to an advanced level of proficiency in NumPy. Whether you're a data scientist, engineer, researcher, or developer, mastering NumPy is essential for efficient data manipulation, scientific computing, and machine learning.

Data is everywhere around us, and making sense of it is extremely important. Visualization helps you deal with data by finding certain patterns and insights in it. You will develop a solid foundation of data visualization using Python and its libraries, such as matplotlib and seaborn, to get as much information from data as possible in a neat and concise way.

Master the essentials of working with databases in Python using sqlite3 and SQLAlchemy. Learn to store, modify, and retrieve data efficiently, build optimized queries, and connect your applications to databases. Gain practical experience in both SQL and ORM approaches to manage data through clean, Pythonic workflows.

Unlock the power of regular expressions in Python with our comprehensive course designed for both beginners and experienced developers. This course will take you through the essential functions of the re module, including search, findall, finditer, and more, using practical examples and hands-on exercises. You'll learn how to extract and manipulate text data efficiently, enabling you to tackle complex string processing tasks with confidence. Whether you're looking to enhance your data analysis skills or streamline your coding workflow, this course provides the tools and knowledge to master regular expressions and elevate your programming capabilities.

This is a hands-on course that will help you understand the basics of object-oriented programming in Python. You will learn how to create classes, work with objects, use inheritance, and extend the capabilities of your programs.

We will use pandas to analyze departmental data by exploring, cleaning, and manipulating the dataset. Starting with basic inspection and data cleaning, we'll perform filtering, merge datasets, apply advanced filtering using multiple conditions, and finally group the data to extract meaningful insights.

In the world of business, making decisions based on hard data rather than intuition can be the key to success. This course focuses on one crucial technique: analyzing A/B test data. The centerpiece of the course is a project where you'll conduct a detailed analysis of an A/B test. This project, which you can showcase in your CV, is hosted on Codefinity, allowing you to continually refine it and demonstrate your growing expertise.

Learn practical techniques to clean, transform, and engineer data for machine learning using Python. This course covers essential preprocessing steps, feature creation, and hands-on challenges to prepare data for modeling.

Master the art of exploratory data analysis (EDA) using Python, pandas, matplotlib, and seaborn. Learn to extract insights, visualize patterns, and communicate findings effectively using a consistent retail dataset.

A comprehensive course designed for students with strong math backgrounds and intermediate to advanced Python skills, focusing on leveraging SciPy for scientific computing, optimization, integration, and advanced mathematical operations.

A practical course designed for math students to harness the power of Python for solving mathematical problems, visualizing data, and applying computational thinking to real-world scenarios. Each section blends engaging theory with hands-on challenges, focusing on mathematical applications and problem-solving.

A practical course designed for researchers who want to leverage Python for data analysis, visualization, and scientific computation. The course focuses on real-world research scenarios, using Python and its scientific libraries to solve common research problems, analyze data, and present findings effectively.