Speaking as a hiring manager, it doesn’t take much to stand out as a candidate for a statistical programming job. We just finished hiring the The post Resume & Interview Tips For R Programmers appeared first on ProgrammingR.

Building a Shiny App to explore the model and the data About the Shiny App In my previous post I built several models to try to predict the amount of residential solar installed per county by quarter as a function of solar insolation, price of solar electricity, county population and county median income. To explore

Predicting the residential solar power installations by county by quarter in CA from 2009-2013 So far I have gathered three data sets and combined them into one which I will now use to try to predict the number of solar installations by county by quarter in CA from 2009-2013. The three data sets I am

Data Mining the California Solar Statistics with R: Part III Today I want to combine the California solar statistics with information about the annual solar insolation in each county as well as information about the population and median income. These can then be used as predictors in the models I'll build in the next post.

Data Mining the California Solar Statistics with R: Part II In today's post I'll be working some more with the working data set from California Solar Statistics. Last time I imported the data, cleaned it up a bit, grouped it by county and year, and made some plots to look at how residential solar installations

Data Mining the California Solar Statistics with R: Part I Intro Today I’m taking a look at the data set available from California Solar Statistics availalbe from https://www.californiasolarstatistics.ca.gov/. This data set lists all the applications for state incentives for both residential and commercial systems, it contains information about the PV (Photovoltaic) system size, location, cost,

Here is the code that fixed up the World Bank data export for use in Tableau. The databank spits out everything in an untidy format for grouping and aggregating. The reshape2 and plyr packages make it easy to manipulate the whole set … Continue reading →

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