PV Watts Scripting

We want to perform our time of use computation with the value of the solar electricity but using Python to perform calculations rather than a spreadsheet.

Tools

Try Jupyter is an browser-based online development environment that we will use for Python. Students have had the best success using the Chrome browser for this.

• Try Jupyter

Pandas is a python library for panel data. We can think of it like a spreadsheet replacement.

• Pandas

Numpy, is a python library for numerical computations. It provides mathematical functions and algorithms for computation.

• Numpy

Array Programming

Using Pandas and Numpy we can do math on an entire column of data with one command. This is different than making a copy of the formula for every row in the spreadsheet.

Group By

To sum the data by month, we will use the group by function.

We group a data column (energy or power) by another data column (the month) and then perform a computation on the separate groups (a sum of each month).

This is called a group by, or a split-apply-combine.

If-Then programming

To perform if-then using array programming, there is a function called where.

This works similar to what we did in the spreadsheet.

data.where(cond, {this value if true}, {this value if false})