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
pd_df = timeseries.to_pandas_dataframe()
# Convert to Polars data frame
pl_df = timeseries.to_polars_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.
1 maintainer
Metadata
1 maintainer
Release files for energyquantified 0.18
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