UCB DATA - team project 1
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Project Title: Solar Adoption Analysis for New York State Between 2000 and 2017
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Team Members: Dipesh, Josh, Aubrey, Vish
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Project Description/ Outline: To analyze the proliferation of solar energy projects in New York state across an 18 year period factoring in project costs, socio-economic factors per zipcode, and the introduction of financial innovations in the market as influences on area of adoption per zipcode and concentration of projects.
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Reserach Questions to Answer: (1) How solar adoption--and its associated costs--have evolved over time.
- How has the penetration of solar energy evolved over time for residential, non-residential, and utility scale solar energy projects?
- Where is the adoption of solar concentrated (display this as a heat map with adoption per 1000 as a heatmap)?
- How has the cost of rooftop solar equipment changed over time w/ and w/o incentives? (2) What the relationship is between several socio-economic (SEC) factors and solar penetration within various zipcodes.
- How are income levels related to solar adoption? (Analysis at zip level. Use census data to analyze relationship between % home ownership, income, and solar adoption) (3) Whether or not solar adoption changes are correlated with the introduction of finacial innovations in the market
- Did solar adoption change with the introduction of financial innovations (lease/power purchase agreements versus own)? (4) A sentiment analysis re: how social media users feel about the top 10 solar panel contractors in NY.
- How do Twitter users feel about the top 10 solar contractors w/in New York?
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Data Sets to be Used:
- Rooftop solar installation data (data.ny.gov) - data on 83.7k projects, with lots of detail
- US Census Bureau Data (for socieconomic indicators by zip code)
- Twitter API data
- IEA/ NYISO data (www.eia.gov) (Based on narrower set of questions, we may not need this)
- Rough Breakdown of Tasks: Solar Data 1 Read in NY solar data 2 Narrow down to analysis data 3 Produce a dataset summaryizing key variables by year-month and customer type 4 Produce a dataset summarizing key variables by zip code 5 Identify the top 10 solar installer in NY
Census Data Read census documentation Read in relevant variables for NY zip code store zip level dataset
Prepare zip-code level shape files
Twitter Data collection Read in 500 tweets each for each of the top 10 installers in NY -Filter data (if needed - e.g. avoid tweets by installer) -Perform sentiment analysis Address research questions -What is the penetration of solar (the S-curve) and is it still growing? Does it vary for residential rooftop, non-residential rooftop, and solar farms?
- How does it vary by location (kw per 10,000)? Is it concentrated in specific locations?
- How have the costs of solar changed over time? with and without incentives?
- Did solar adoption change with the introduction of financial innovations (lease/ppa versus own)
- How are income levels related to solar penetration?
- How are home ownership rates related to solar penetration (and income levels)?
- How do NY twitter users feel about the top solar installer in NY?
Quality checks on code
Swap code and review Merge code
Prepare presentation
Intro 2 Key research questions Data sources 2 Results 2 Additional research 2
Practice presentation
- What each team member wants to get from this project:
- Dipesh: wants to get hands-on experience working with data (collection, processing/ analysis).
- Josh: wants to work on the plotting/ visualizations.
- Aubrey: wants to improve coding skills as well as create a portfolio piece.
- Vish: wants to do participate in data collectin, cleaning, analysis, and visualiztion using python.