Skip to main content
The ESIOS API provides access to hundreds of energy market indicators. This guide shows you how to explore the catalog and find the indicators you need.

​
Listing All Indicators

Retrieve the complete catalog of available indicators: 
from esios import ESIOSClient

client = ESIOSClient(token="your_api_key")

# Get all indicators as a DataFrame
indicators = client.indicators.list()

print(f"Total indicators: {len(indicators)}")
print(indicators.head())
The catalog is cached locally for 24 hours by default, so subsequent calls are fast and don’t hit the API.

​
Searching by Name

Use the search() method to find indicators by name (case-insensitive substring match): 
# Find all price-related indicators
price_indicators = client.indicators.search("precio")

print(price_indicators[["name", "short_name"]])
The search method looks for matches in the indicator name field, supporting partial matches. For example, searching for “pvpc” will find all PVPC tariff indicators.

​
Common Search Patterns

# Find day-ahead market prices
market_prices = client.indicators.search("mercado diario")

# Filter to specific market price
pvpc = client.indicators.search("pvpc")

​
Viewing Indicator Details

Once you find an indicator, get detailed information: 
# Get indicator handle
handle = client.indicators.get(600)  # 600 = Precio mercado diario

print(f"ID: {handle.id}")
print(f"Name: {handle.name}")
print(f"Available geographies: {len(handle.geos)}")

# View all metadata
import json
print(json.dumps(handle.metadata, indent=2))

​
Exploring Indicator Catalog

Filter and sort the catalog to find relevant indicators: 
import pandas as pd

# Get full catalog
df = client.indicators.list()

# Show indicators with 'price' in name
price_df = df[df['name'].str.contains('precio', case=False, na=False)]

# Sort by ID
price_df_sorted = price_df.sort_index()

print(price_df_sorted[['name', 'short_name']].head(10))

​
Working with Multi-Geography Indicators

Some indicators provide data for multiple countries or regions: 
# Indicator 600 includes multiple European countries
handle = client.indicators.get(600)

# View available geographies
geos_df = handle.geos_dataframe()
print(geos_df)

# Output:
#   geo_id        geo_name
# 0      3          España
# 1   8741        Portugal
# 2   8742         Francia
# 3   8743  United Kingdom
Geography information is cached per-indicator, so you can work offline once metadata has been fetched.

​
Next Steps

Once you’ve found your indicator:

Build docs developers (and LLMs) love

Get started for freeTalk to us