The package “maps” contains geographical information very useful for producing maps, and it’s fairly easy to use this to make plots in ggplot2. This is a short tutorial showing how to create a map with shaded areas, like the one below.
DataSF hosts government data released by the city and county of San Francisco. Among all the data sets in its collection, it has a data sets showing the name, description, tags, etc of all the data sets in DataSF. “DataSF Data Set Tags” is a quick visualization of the tags in DataSF.
I wanted to play with Protovis for a while, and The Bay Citizen Code-a-Thon was the perfect opportunity to do so. So far I found Protovis to be pretty easy to use, with an ample of examples to
copy study from. The graphics it creates are quite elegant as well.
In the second half of part 1 of this series, we looked at the type of projects that donors prefer by studying the projects that are more likely to become fully funded. An equally important factor to consider is return donorship. About one in three donors make subsequent donations within one year of their first. Having returning donors mean that donors were happy about the impacts they made, and that future projects are more likely to be funded. In part 3, we look at factors affecting whether a first-time donor would return and continue to contribute to DonorsChoose.
For the purpose of this analysis, new donors are considered to have “returned” if they made new contributions on DonorsChoose within the next 365 days.
Percentage return donorship have declined a little in the past few years, dipping down from 35% in 2008 to a little less than 30% in 2010. (There is some abnormality in the year 2006; it is unclear why this is the case.)