pyedautils 0.0.11

Python Energy Data Analysis Utilities

pyedautils

Python Energy Data Analysis Utilities

What is it?

pyedautils is a python package designed for analyzing and visualizing comfort and energy time series data. It provides a compact yet expanding collection of utility functions and visualizations aimed at streamlining data exploration.

Installation

The package is available on PyPi.org and can be installed with:

pip install pyedautils

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Table of contents

plots.py

• plot_daily_profiles_overview()

data_io.py

• save_data()
• load_data()

geopy.py

• get_lat_long()
• get_altitude_lat_long()
• convert_wsg84_to_lv95()
• get_altitude_lv95()
• get_coordindates_ch_plz()
• get_distance_between_two_points()

meteo_swiss.py

• find_nearest_station()

season.py

• get_season()

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plots.py

plot_daily_profiles_overview()

This function creates an overview of typical daily profiles per weekday and season of year with a confidence band where 90% of the values lie (q5 to q95).

from pyedautils.data_io import load_data
from pyedautils.plots import plot_daily_profiles_overview

# data preprocessing
file_path = "pyedautils/data/ele_meter.csv"
df = load_data(file_path)
df['value'] = df['value'].diff()
df = df.dropna()

# create and show plot
fig = plot_daily_profiles_overview(df)
fig.show(renderer="browser")

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data_io.py

File handling utilities for loading and saving data.

save_data()

Saves data to a file in various formats (CSV, Pickle, JSON) based on the given file extension of pile_path.

from pyedautils.data_io import save_data

file_path = "./my_filename.json"
save_data(df, file_path)

load_data()

Loads data from a file in various formats (CSV, Pickle, JSON) based on the given file extension of file_path.

from pyedautils.data_io import load_data

file_path = "pyedautils/data/ele_meter.csv"
df = load_data(file_path)

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geopy.py

Helper funtions to find the coordinates from an address, convert lat/long values to swiss WGS84 coordinates and get the altitude from coordinates.

get_lat_long()

Returns latitude and longitude coordinates for the given address.

from pyedautils.geopy import get_lat_long

get_lat_long("Technikumstrasse 21, 6048 Horw, Switzerland")

# Out: [47.0143233, 8.305245521466286]

get_altitude_lat_long()

Returns altitude in meters above sea level for the given WGS84 coordinates. The opentopodata.org api gets used.

from pyedautils.geopy import get_altitude_lat_long

get_altitude_lat_long(47.0132975, 8.3059169)

# Out: 444.9

convert_wsg84_to_lv95()

Converts WGS84 latitude and longitude coordinates to Swiss coordinate system LV95.

from pyedautils.geopy import convert_wsg84_to_lv95

convert_wsg84_to_lv95(47.0132975, 8.3059169)

# Out: [2665945.104007165, 1207280.4252477456]

get_altitude_lv95()

Returns altitude in meters above sea level for the given LV95 coordinates. The geo.admin.ch api gets used.

from pyedautils.geopy import get_altitude_lv95

get_altitude_lv95([2665960.531, 1207281.985])

# Out: 442.6

get_coordindates_ch_plz()

Returns latitude and longitude for a Swiss postal code.

from pyedautils.geopy import get_coordindates_ch_plz

get_coordindates_ch_plz(6048)

# Out: (47.0108, 8.3039)

get_distance_between_two_points()

Calculates the distance in km between two points on the Earth's surface given their latitude and longitude coordinates.

from pyedautils.geopy import get_coordindates_ch_plz, get_distance_between_two_points

coord1 = get_coordindates_ch_plz(6048) # Horw
coord2 = get_coordindates_ch_plz(3800) # Interlaken

get_distance_between_two_points(coord1, coord2)

# Out: 50.301

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meteo_swiss.py

find_nearest_station()

Returns station id of closest meteo swiss station to a coordinate.

from pyedautils.meteo_swiss import find_nearest_station
from pyedautils.geopy import get_coordindates_ch_plz, get_altitude_lat_long

coord = get_coordindates_ch_plz(6197)
altitude = get_altitude_lat_long(coord[0], coord[1])

find_nearest_station(coord[0], coord[1], altitude, sensor="temp")

# Out: "FLU"

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season.py

get_season()

Get the season name out of a date for filter and grouping purposes.

from pyedautils.season import get_season
from datetime import datetime

get_season(datetime(2024,5,5))

# Out: 'Spring'

Default language of the returned strings is English. You can change that by passing the argument labels:

get_season(datetime(2024,5,5), labels=["Frühling", "Sommer", "Herbst", "Winter"])

# Out: 'Frühling'

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Build info

# open anaconda console and navigate to pyedautils
py -m build
pip install 

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Disclaimer
The author declines any liability or responsibility in connection with the published code and documentation.

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