Python for Energy — Basic
Learn to manipulate energy market data with Python, automate Excel reports, query PostgreSQL databases, and process XML files. Hands-on with real OMIE/e·sios data.
Jesús LópezWhat you'll learn
Energy data analysis
Manipulate time series of prices, generation and consumption with pandas and plotly
PostgreSQL integration
Query and load energy market data directly from Python
Automated Excel reports
Generate formatted multi-sheet reports with xlwings from database data
AI-assisted coding
Use Claude/ChatGPT as a coding copilot throughout the course
Course curriculum
Estimated schedule — dates confirmed when an edition launches
- Installing VS Code
- Creating folders and files in VS Code
- Miniconda on macOS
- Miniconda on Windows
- Python & Jupyter Lab on macOS
- Jupyter Lab on Windows
- Basic data types: numbers, strings, lists, dictionaries
- Variables and operators
- Control structures: if, for, while
- Functions and modules
- Practice: personalized greeting script
- Reading data from CSV, Excel and flat files
- DataFrames: creation, access and manipulation
- Filtering, grouping and aggregation
- Time series: date indexing, resample, rolling averages
- Data cleaning and null value handling
- Practice: energy price evolution chart
- Connecting with psycopg2 and sqlalchemy
- Basic queries: SELECT, WHERE, GROUP BY
- Import results into pandas / export to SQL
- Practice: average spread between day-ahead and auction prices
- Using pandas.to_excel and xlwings
- Sheet formatting: column names, index, multiple sheets
- Practice: Excel report with forecasts, production and prices
- Using os and shutil to move, copy and rename files
- Reading multiple files in a directory
- Practice: batch CSV processing with date-organized output
- Using xml.etree.ElementTree
- Creating elements and attributes
- Practice: generate day-ahead market offer XML
- Full pipeline: DB → pandas → analysis → Excel + XML 1.5h
Who is this course for?
Energy professionals
Working with market data from OMIE, e·sios, or similar sources
Analysts
Looking to automate manual Excel reporting and data processing
Teams
Needing to integrate Python with databases and XML market files
Prerequisites
No programming experience required
Frequently asked questions
What's included
Dedicated PostgreSQL database
With real energy market data from OMIE and e·sios
Interactive notebooks
Exercises and solutions for each module
Session recordings
Access recordings to review at your own pace
AI as coding copilot
Use Claude/ChatGPT throughout the course to accelerate learning
Price
Contact us
Your instructor
Jesús López
Instructor & Tool Builder
Jesús López builds tools that automate daily tasks—from processing thousands of Excel files to organizing entire projects. With over 54,000 students on LinkedIn Learning, he has a passion for teaching others how to create their own solutions, no programming background needed.
54,000+ students · 3 LinkedIn Learning courses
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