Data Analytics with Python Training – 32’nd Week Recap

Date: 02’nd February 2025 (Sunday)
Time: 9:30 AM to 1:00 PM

Venue:
VGLUG Foundation
SRIMAA PRESCHOOL (Gov Recognized)
Landmark: Opposite to BSNL Exchange
Villupuram 605602

Minutes of meeting

Data Analytics with Python Team 1 (Arts & Science)

Topics:

session 1: Pandas Functions – Vijayalakshmi

Session 2: Docker – Deepak

Pandas Functions

Vijayalakshmi’s session provided a practical introduction to Pandas, a cornerstone of data analysis in Python. She covered essential functions for data manipulation, including:

Data Loading and Inspection: read_csv(), read_excel(), head(), tail(), info(), describe()
Data Cleaning: isnull(), dropna(), fillna(), duplicated(), drop_duplicates()
Data Selection and Indexing: loc[], iloc[], at[], iat[]
Data Manipulation: sort_values(), groupby(), merge(), concat()
Data Transformation: apply(), map(), astype()

Participants gained hands-on experience working with DataFrames and Series, learning how to clean, transform, and analyze data effectively.

Docker

Deepak’s Docker session demystified containerization technology. He covered:

Docker Fundamentals: Images, containers, Dockerfile, Docker Compose
Building and Running Containers: Creating images from Dockerfiles, running containers, managing container lifecycles
Networking and Volumes: Connecting containers to networks, using volumes for persistent storage
Use Cases: Discussed the benefits of Docker for application deployment, portability, and scalability.

Participants learned how to containerize applications, enabling them to run consistently across different environments.

Data Analytics with Python Team 2 (Arts & Science)

Topics:

session 1: Pandas Functions – Sathish Kumar

Session 2:Docker – Vignesh

Pandas Functions

Sathish Kumar’s session focusing on practical Pandas usage for data manipulation. He likely covered similar functions and techniques, providing another perspective on working with DataFrames and Series.

Docker

Vignesh’s Docker session provided an introduction to containerization. He likely covered similar topics as Deepak’s session, including image creation, container management, and the benefits of using Docker.

Data Analytics with Python Team 1 & 2 (Engineering)

Topics:

session 1: Pandas and NumPy Introduction – Deepak

Session 2: Docker – Mathusoothanan’s

Pandas and NumPy Introduction

Deepak’s combined session introduced two fundamental Python libraries for data science:

NumPy: Covered array creation, array operations (arithmetic, slicing, indexing), mathematical functions (linear algebra, statistics), and the benefits of using NumPy arrays for numerical computations.

Pandas: Introduced DataFrames and Series, covering data loading, inspection, cleaning, and basic manipulation techniques.

This session laid the groundwork for further data analysis work.

Docker

Mathusoothanan’s Docker session provided a comprehensive overview of containerization. He likely covered:

Docker Architecture: Explanation of Docker Engine, images, containers, and registries.
Docker Commands: Hands-on practice with common Docker commands for building, running, and managing containers.
Docker Networking: Configuring network connections between containers.
Docker Volumes: Using volumes for data persistence.

Participants gained practical skills in using Docker for application deployment.

DevOps

Topics:

session 1: Ansible Introduction Vignesh

Session 2: Discussion about Android and Web Application Development – Prathap

Ansible Introduction

Vignesh’s Ansible session introduced the team to automation for configuration management and deployment. He covered:

Ansible Architecture: Control node, managed nodes, inventory files, playbooks, modules.
Writing Playbooks: Creating YAML-based playbooks to define automation tasks.
Using Modules: Exploring various Ansible modules for managing systems, software, and configurations.
Ansible Best Practices: Tips for writing efficient and maintainable Ansible code.

Participants learned how to automate repetitive tasks, improving efficiency and consistency.

Discussion about Android and Web Application Development

Prathap led an engaging discussion on the current landscape of Android and web application development. Key topics likely included:

Mobile Development: Android SDK, Kotlin/Java, UI design principles, app publishing.
Web Development: Front-end technologies (HTML, CSS, JavaScript), back-end frameworks (e.g., Python/Django, Node.js), databases, API design.
Emerging Trends: Discussions on new technologies, frameworks, and best practices in both mobile and web development.

This session facilitated knowledge sharing and brainstorming on development strategies.

Acknowledgements:

A big thank you to all the presenters: Sathishkumar, Dilip, Deepak, Madhusoodhan, Kowsalya, Loganathan, Vijayalakshmi, Vignesh, and Prathap for their valuable contributions. The sessions provided a great opportunity for learning and collaboration across teams.

Here. we attached the meetup clicks.

Devops