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I want to look at installations of solar panels on home rooftops in the US, as a compliment to my previous project about community solar gardens.
Not sure how I missed this during the last solar project, but I've found the Natl. Renewable Energy Laboratory's online database of solar panel installation in US (NREL is an arm of the Dept. of Energy). This breaks down by type of installation, so I'm able to see which were residential. It's a huge dataset overall (more than a million installations), so for now I've gotten data from this year's installations and last's.
Summary
I don't have any strong ideas yet on visualization. My new solar data only has zip codes rather than lat & long, so my mapping ability may be a bit more limited. Here's one thing that seems possible, since I have the categorical breakdown of type of solar panel installation (commercial, residential, utility, etc).
Possible problems/fears/questions:
Like the last solar project, I don't have a specific narrative in mind; I'm basically trying to find out the general status of the solar industry, mostly at the consumer level. We'll see where it goes.
Work so far
I have done a couple searches in the database and downloaded the csv's, brought them into pandas and done some very initial poking around.
Checklist
I have already spent time with my data set, opening it, exploring it, etc
I have created a "DIARY.md" file to save links and list all of the terrible, no good problems I come across
My issue links to my data set(s)
My issue links to my code repository
My issue explains what I'd like to explore in the data set
My issue includes images - either inspiration or what I've done so far
The text was updated successfully, but these errors were encountered:
I still don't have any visuals yet -- additional work on the project has been on some new data, which the solar trade group Solar Energies Industry Association sent to me after I reached out to them. It's a dataset of just residential solar installations, which is kind of what I was after originally; my previous new datasets were sliced out of the NREL database in small yearly bits for the sake of maintaining manageable size. I've now got the new data into pandas. It should be a really nice base to do some graphs on residential solar installs since 2010, and I can supplement as needed with the NREL data, which has some slightly different info.
Any changes in direction or topic?
Stronger focus on residential solar with the new data.
Problems/Questions
Checklist
I have included my visuals
I have filled out the sections above
I have been updating my DIARY.md with details about my process
I have uploaded/updated any Jupyter Notebooks or other datasets into my code repository
Pitch
I want to look at installations of solar panels on home rooftops in the US, as a compliment to my previous project about community solar gardens.
Not sure how I missed this during the last solar project, but I've found the Natl. Renewable Energy Laboratory's online database of solar panel installation in US (NREL is an arm of the Dept. of Energy). This breaks down by type of installation, so I'm able to see which were residential. It's a huge dataset overall (more than a million installations), so for now I've gotten data from this year's installations and last's.
Summary
I don't have any strong ideas yet on visualization. My new solar data only has zip codes rather than lat & long, so my mapping ability may be a bit more limited. Here's one thing that seems possible, since I have the categorical breakdown of type of solar panel installation (commercial, residential, utility, etc).
Details
Possible headline(s):
Data set(s): NREL's Open PV Project
Code repository: https://github.com/mattrehbein/data_studio/tree/master/code/07-project
Possible problems/fears/questions:
Like the last solar project, I don't have a specific narrative in mind; I'm basically trying to find out the general status of the solar industry, mostly at the consumer level. We'll see where it goes.
Work so far
I have done a couple searches in the database and downloaded the csv's, brought them into pandas and done some very initial poking around.
Checklist
The text was updated successfully, but these errors were encountered: