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 López Jesús López
10.5 Hours4 Sessions6 Modules
New edition coming soon March 31, 2026

What 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

11 modules 34 lessons
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
Demo: market data analysis 30 min
Demo: automated Excel report 30 min
Environment verification 30 min
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

A laptop with admin access to install software Required
Internet connection for database access 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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