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Fetch multiple indicators and merge them into a single DataFrame for cross-indicator analysis
from esios import ESIOSClient
client = ESIOSClient()
compare() returns a MultiIndex column (indicator_name, geo_name) — one column per indicator×geo combo:
df = client.indicators.compare(
[600, 612],
start="2025-01-01",
end="2025-01-07",
)
df
indicator Precio mercado SPOT Diario \
geo Portugal Francia España Alemania
datetime
2025-01-01 00:00:00+01:00 134.49 12.36 134.49 2.16
...
[672 rows × 8 columns]
geo_ids, each indicator returns a single column, so the result has flat columns named by indicator:
handle = client.indicators.get(600)
spain_id = handle.resolve_geo("España")
df = client.indicators.compare(
[600, 612, 613, 614],
start="2025-01-01",
end="2025-01-07",
geo_ids=[spain_id],
)
df
Precio mercado SPOT Diario Precio mercado SPOT Intradiario Sesión 1 ...
datetime
2025-01-01 00:00:00+01:00 134.49 129.89 ...
...
[672 rows × 4 columns]
df.plot(figsize=(14, 5), title="Market Session Prices — España (€/MWh)")
df.describe().round(2)
Precio mercado SPOT Diario Precio mercado SPOT Intradiario Sesión 1 ...
count 672.00 672.00
mean 92.74 93.22
std 43.26 42.73
min 3.52 -0.01
25% 58.04 57.50
50% 100.42 102.00
75% 126.60 124.29
max 161.10 163.99