Utilities to manipulate csv files from EnergyPlus

EnergyPlus output file are messy and slow to manipulate in a spreadsheet, so some methods are developed to visualize, filter, etc the csv file.

A jupyter notebook is provided with typical output file.

Getting Started

Download the notebook using-Eplus.ipynb, an example of each method is used. The file Eplus.py must be saved in the folder "modulos" and the data csv files go to folder data.

Prerequisites

Pandas
Bokeh

Using

from modulos import Eplus as ep from bokeh.plotting import figure, output_file, show from bokeh.io import output_notebook output_notebook()

nombres = ['t','Ein','Eout', 'Nin','Nout', 'Oin','Oout', 'Sin','Sout', 'Pin','Pout','Tein','Teout'] caso1 = ep.readEP('datos/cubo.csv',nombres)

caso1.datos.columns

p = figure(plot_width=900, plot_height=500,x_axis_type='datetime', toolbar_location="above") formato de inicio y fin YYYY-MM-DD inicio = '2017-04-06' fin = '2017-04-07'

q = caso1.datos[inicio:fin]

p.line(q.index,q.Ein,color='blue',legend='Ei') p.line(q.index,q.Eout,color='red',legend='Eout') p.line(q.index,q.Pin,color='black',legend='Pi') p.line(q.index,q.Pout,color='brown',legend='Pout') show(p)

Authors

• Guillermo Barrios - Initial work - GEE-UNAM
• Maximiliano Valdez - Espiritual leadership - IER-UNAM

License

This project is licensed under ...

Acknowledgments

• Requests are welcomed