Overview#
Goal
Display a 4x7 grid of daily electricity consumption profiles, organized by season (rows) and weekday (columns), to reveal seasonal and weekly patterns.
Data Basis
Electricity data (ele_meter.csv) bundled with the pyedautils package: the mean electric power of a household in W per 15-minute interval (the 15-minute consumption in Wh × 4), for 2015.
Data Preparation#
import pandas as pd
from importlib import resources
data_path = resources.files("pyedautils") / "data" / "ele_meter.csv"
df = pd.read_csv(data_path, sep=";")
df.head()
| timestamp | value | |
|---|---|---|
| 0 | 2015-01-01 00:00:00 | 40.0 |
| 1 | 2015-01-01 00:15:00 | 32.0 |
| 2 | 2015-01-01 00:30:00 | 32.0 |
| 3 | 2015-01-01 00:45:00 | 34.0 |
| 4 | 2015-01-01 01:00:00 | 34.0 |
Visualization#
from pyedautils.plots import plot_daily_profiles_overview
fig = plot_daily_profiles_overview(
data=df,
title="Electricity Meter - Daily Profiles",
ylab="Power [W]",
confidence=95.0,
)
fig.show()
Customization
The plot_daily_profiles_overview function accepts the following optional parameters:
confidence: Set the confidence interval band (e.g.,95.0for 95%).colors: Customize the color scheme.
fig = plot_daily_profiles_overview(df, title="Custom Example", ylab="Power [W]", confidence=90.0)