ebtools 0.1.0

Helper functions and data for electricity market data workflows.

ebtools

ebtools is a Python helper package for electricity market and energy-industry data analysis workflows.

It provides centralised utility functions for common data preparation tasks such as datetime parsing, dataframe filtering, settlement period and EFA handling, array selection, and file export. The package is intended to support other analysis tools rather than perform one specific end-to-end analysis task itself.

Installation

Install from PyPI:

pip install ebtools

Then import the package:

import ebtools as ebt

Requirements

ebtools requires Python 3.11 or later.

Core dependencies include:

• NumPy
• pandas
• pytz
• pyarrow
• fastparquet
• openpyxl

Usage Examples

Parse Datetime Columns

import pandas as pd
import ebtools as ebt

df = pd.DataFrame(
    {"Date": [
        "2024-03-14",
        "15/03/2024",
        "21/11/2023",
        "2024-05-01"
        ]}
    )

df_result = ebt.check_datetime_formats(
    df,
    colname="Date",
    format_list=["%Y-%m-%d", "%d/%m/%Y"],
)

        Date
0 2024-03-14
1 2024-03-15
2 2023-11-21
3 2024-05-01

Parse Timezone-Aware Datetime Columns

import pandas as pd
import ebtools as ebt

df = pd.DataFrame({"Date": ["2024-03-15T01:30:00+01:00"]})

df_result = ebt.check_datetime_formats_tz(
    df,
    colname="Date",
    format_list_tz="%Y-%m-%dT%H:%M:%S%z",
)

                 Date
0 2024-03-15 00:30:00

Filter A Dataframe

import pandas as pd
import ebtools as ebt

df = pd.DataFrame({
    "Fuel": ["Wind", "Gas", "Wind"],
    "Output": [100, 50, 120],
})

wind = ebt.df_filter(df, colname="Fuel", term="Wind")

   Fuel  Output
0  Wind     100
2  Wind     120

Force A Value To A List

import ebtools as ebt

value = ebt.force_to_list("Wind")

['Wind']

Convert A Date To A Datetime Boundary

import ebtools as ebt

start = ebt.convert_date_to_datetime("2024-03-14", position="start")
end = ebt.convert_date_to_datetime("2024-03-14", position="end")

'2024-03-14 00:00:00'   # start
'2024-03-14 23:59:59'   # end

Convert A Delivery Date And EFA Block To An EFA Datetime

import ebtools as ebt

efa_datetime = ebt.convert_date_to_efa_datetime("2023-03-14", efa=1)

# '2023-03-13T23:00:00'

Save Dataframes To Excel

import pandas as pd
import ebtools as ebt

prices = pd.DataFrame({"Price": [10.5, 11.2]})
volumes = pd.DataFrame({"Volume": [100, 120]})

ebt.save_to_xlsx(
    [prices, volumes],
    location=".",
    file_name="market_data.xlsx",
    sheet_name=["Prices", "Volumes"],
)

Return The Starting Date Of A Week

import pandas as pd
import ebtools as ebt

df = pd.DataFrame({"Date": pd.date_range("2024-01-01", periods=14)})

week_start = ebt.week_starting(
    df,
    week=2,
    year=2024,
    weekday="Mon",
    return_format="%Y-%m-%d",
)

# 2024-01-08

Keep The Largest Values In Each Array Row

import numpy as np
import ebtools as ebt

arr = np.array([
    [3, 1, 2],
    [9, 4, 8],
])

result = ebt.n_largest_values_per_row(arr, largest=1, replace=0)

array([[3, 0, 0],
       [9, 0, 0]])

Development

For local development, install the package in an environment containing the runtime and development dependencies.

Run the test suite with:

PYTHONPATH=src python -m pytest

Project Links

Add these links before publishing if available:

• PyPI project page
• Source repository
• Issue tracker
• Documentation site

License

This project is licensed under the Apache License 2.0. See LICENSE for details.