Before / After Comparison

Goal

Compare energy consumption before and after an optimization event to evaluate its impact.

Data Basis

Monthly energy consumption data (seasonal_monthly.csv) bundled with the pyedautils package. 10 years of monthly values.

Data Preparation

import pandas as pd
from importlib import resources

data_path = resources.files("pyedautils") / "data" / "seasonal_monthly.csv"
df = pd.read_csv(data_path, sep=";")
df.head()

	timestamp	value
0	2010-01-01	19.000000
1	2010-02-01	19.642857
2	2010-03-01	17.032258
3	2010-04-01	8.633333
4	2010-05-01	0.870968

Visualization

from pyedautils.plots import plot_seasonal_before_after

fig = plot_seasonal_before_after(
    data=df,
    date_optimization="2017-09-01",
    title="Before/After Energy Optimization",
    ylab="Mean daily energy [kWh/d]",
)
fig.show()

Customization

The plot_seasonal_before_after function accepts additional parameters:

• date_optimization — The date that separates the “before” and “after” periods (format: "YYYY-MM-DD"). In this example, "2017-09-01" marks the optimization date.

• confidence — Controls the confidence interval shown around the seasonal means. Adjust to widen or narrow the uncertainty band.