Energy Quantified Python Client

Documentation | Python package | GitHub repository

The Python library for Energy Quantified's Time Series API. It allows you to access thousands of data series directly from Energy Quantified's time series database. It integrates with the popular pandas library and the polars libarary for high-performance data analysis and manipulation.

Developed for Python 3.10+.

from datetime import date, timedelta
from energyquantified import EnergyQuantified
Initialize client
eq = EnergyQuantified(api_key='<insert api key here>')
Freetext search (filtering on attributes is also supported)
curves = eq.metadata.curves(q='de wind production actual')
Load time series data
curve = curves[0]
timeseries = eq.timeseries.load(
    curve,
    begin=date.today() - timedelta(days=10),
    end=date.today()
)
Convert to Pandas data frame
pddf = timeseries.topandas_dataframe()
Convert to Polars data frame
pldf = timeseries.topolars_dataframe()

Full documentation available at Read the Docs.

Features

• Simple authentication
• Metadata caching
• Rate-limiting and automatic retries on network errors
• Full-text search and keyword search for curves and powerplants
• Forecasts- and time series data
• Period-based data
• OHLC data with SRMC calculations
• Shows your subscription for each data series
• Support for timezones, resolutions, aggregations and unit conversions
• Easy-to-use filters for issue dates and forecast types
• Push feed for live updates on data modifications
• Integrates with pandas and polars

Note: A user account with an API key is required to use this library. Create an account on Energy Quantified's home page. Trial users get access to 30 days of history.

Installation

Install with pip:

# Install
pip install energyquantified
Upgrade
pip install --upgrade energyquantified

Documentation

Find the documentation at Read the Docs.

License

The Energy Quantified Python client is licensed under the Apache License version 2.0.