GroupBy in Python

In this video, you'll learn about grouping data using the groupby method in Pandas and how it can help transform your dataset for analysis. Here's a summary of the key points covered:

  1. Grouping Data with groupby Method:

    • The groupby method in Pandas is used on categorical variables to group the data into subsets according to the different categories of that variable.
    • You can group by a single variable or by multiple variables by passing in multiple variable names.
    • For example, if you want to analyze the relationship between drive system types (forward, rear, and four-wheel drive) and the price of vehicles, you can group the data by the drive wheels variable.

  2. Calculating Group Statistics:

    • After grouping the data, you can calculate summary statistics for each group, such as the mean, median, or sum.
    • For example, you can find the average price of vehicles for each drive wheel type.

  3. Transforming to a Pivot Table:

    • To make the grouped data easier to understand and visualize, you can transform it into a pivot table using the pivot method in Pandas.
    • Pivot tables display one variable along the columns and another variable along the rows, making it easier to compare different categories.
    • This is similar to pivot tables commonly used in Excel spreadsheets.

  4. Heat Map Plotting:

    • Another way to visualize the pivot table is by using a heat map plot.
    • Heat maps assign a color intensity based on the data values, making it easy to identify patterns and relationships between variables.
    • You can use plotting libraries like Pyplot to create heat maps.
    • In the example provided, the heat map plot displays the average prices of vehicles for different body styles and drive wheel types, with colors indicating price ranges.

By grouping and transforming the data, you can gain insights into how different variables interact and their impact on the target variable, allowing for better analysis and decision-making. 

Comments

Post a Comment

Popular posts from this blog

Common cybersecurity terminology

  As you’ve learned, cybersecurity (also known as security) is the practice of ensuring confidentiality, integrity, and availability of information by protecting networks, devices, people, and data from unauthorized access or criminal exploitation. In this reading, you’ll be introduced to some key terms used in the cybersecurity profession. Then, you’ll be provided with a resource that’s useful for staying informed about changes to cybersecurity terminology. Key cybersecurity terms and concepts There are many terms and concepts that are important for security professionals to know. Being familiar with them can help you better identify the threats that can harm organizations and people alike. A security analyst or cybersecurity analyst focuses on monitoring networks for breaches. They also help develop strategies to secure an organization and research information technology (IT) security trends to remain alert and informed about potential threats. Additionally, an analyst work...
Read more

Introduction to security frameworks and controls

  Imagine you're working as a security analyst and receive  multiple alerts about suspicious activity on the network.  You realize that you'll need to implement  additional security measures to keep  these alerts from becoming  serious incidents. But where do you start? Play video starting at ::17 and follow transcript 0:17 As an analyst, you'll start by identifying  your organization's critical assets and risks.  Then you'll implement  the necessary frameworks and controls. Play video starting at ::27 and follow transcript 0:27 In this video, we'll discuss how security professionals  use frameworks to continuously identify and manage risk.  We'll also cover how to use  security controls to manage or reduce specific risks. Play video starting at ::40 and follow transcript 0:40 Security frameworks are guidelines  used for building plans  to help mitigate risks and threats to data and privacy.  Security frameworks ...
Read more

syllabus

Cybersecurity program: Year 1: Foundation Courses Semester 1: Introduction to Cybersecurity Fundamentals of Information Technology Programming Basics (Python, C++) Discrete Mathematics Digital Logic Design Lab Work (Programming, IT Fundamentals) Semester 2: Data Structures and Algorithms Computer Networks Operating Systems Cyber Law and Ethics Probability and Statistics Lab Work (Data Structures, Networks) Year 2: Core Cybersecurity Courses Semester 3: Network Security Cryptography Database Management Systems Web Technologies Software Engineering Lab Work (Network Security, Cryptography) Semester 4: Ethical Hacking Secure Coding Practices Wireless and Mobile Security Cyber Forensics Human-Computer Interaction Lab Work (Ethical Hacking, Forensics) Year 3: Advanced Cybersecurity Topics Semester 5: Advanced Cryptography Intrusion Detection and Prevention Systems Cloud Security Risk Management and Compliance Elective I (e.g., Blockchain Security, IoT Security) Lab Work (Intrusion Detection...
Read more