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  • Course Length:
  • 2 Days Instructor Led

Telecom networks are continuing to transform in fundamental ways - cloud platforms are enabling networks to be run as software-based functions. This enables the management of these networks to become software centric and thus require the use of scripting and software-oriented approaches to automate and manage tasks performed on these networks. Besides the network, all industries are starting to leverage feature-rich tools that analyze massive, varied data sets to complete tasks more productively and effectively. The Data Automation Workshop is designed for non-programmers who would like to learn to install and use Python. By using hands-on programming exercises, it takes the student on a practical guided tour of Python’s capabilities and throughout the session create several practical and useful Python programs.

Required Equipment
• Students will need a laptop with MS-Excel and Python

This workshop is intended for anyone (non-programmers) who wants to build knowledge and skills related to leveraging data tools to be more productive.

After completing this workshop, the student will be able to:
• Analyze a problem and design step-by-step ways to automate the task at hand
• Learn how to manage data in different forms of data structures to load and manipulate data
• How to use key control structures to manage the process flow
• Implement solutions based on string manipulation, regular expression processing and loops
• Implement a data processing exercise using control and data structures including file operations
• Implement text file and Excel file handling for Input/Output processing
• Learn how to automate data collection through other Web and Application APIs
• Python is used as the programming language for all exercises

1. Setting the Table
1.1. Getting started with Python
1.2. Modules and Functions
1.3. Programming constructs
1.3.1. Conditional statements
1.3.2. For and while loops
1.4. Common data structures
1.4.1. Lists
1.4.2. Dictionary
1.5. String Operations
Exercise: Construct Lists and Dictionary

2. Processing Data from Text Files
2.1. Text File Processing basics
2.2. Command line arguments in Python
2.3. Python File Operations
2.4. File reading and writing
2.5. Python to walk a directory
2.6. Counting lines, words
Exercise: Read a file, count lines, words and develop word length vs. frequency data

3. Processing Data from Excel Workbooks
3.1. What is Openpyxl?
3.2. Installing Openpyxl module
3.3. Creating a Workbook
3.4. Reading data from a Workbook
3.5. Creating and naming Worksheets
3.6. Deleting a Worksheet
3.7. Excel Object Structure
3.8. Reading and writing to/from a cell
3.9. Inserting Formulas into Excel Sheets from Python Programs
3.10. Formatting rows and columns
3.11. Inserting Excel Charts in Python
3.12. Saving an Excel Workbook
Exercise: Create an Excel file, insert data from text file processing and plot a chart

4. Data gathering from Websites and Applications
4.1. Concept of APIs
4.2. Using APIs in Python
4.3. Invoke API on a Web Server
4.4. Capture the response
4.5. Save the response to a file
4.6. Invoke API on an App Server
4.7. Capture the response
4.8. Save the response to a file
Exercise: Invoke APIs from Python

Suggested Prerequisites

• Basic knowledge of Excel