What makes much of Big Data extremely useful is the ability to integrate geospatial information, especially when tracked with time. To that end, ArcGIS is a "must have", and Python is a practical language that allows one to manipulate large data sets such as those found in databases, and that gathered via data acquisition module streams.
While the "cookbook" part of the title is a bit of a misnomer, Programming ArcGIS 10.1 with Python by Eric Pimpler and published by Packt Publishing does include very a total of 75 helpful recipes presented in a logical task-oriented sequence which take advantage of ArcGIS 10 features. It's useful for entrepreneurs who are coming up with innovative data mining solutions to help organizations and individuals in decision-making in many different fields and applications.
What I find most helpful is the fact that the organization of the book takes a building block approach which is helpful for someone who may need to get started, and equally so for someone who would like to simply pinpoint and extract what they want and need.
Here are some of the useful features:
* automated map production and printing: can automate the production of map production and printing (including exporting PDFs), which is helpful when creating a set of maps or map files.
* quickly using geoprocessing tools: this is a quick way to increase functionality and power without having to do everything separately; application-level environment settings are utilized quite helpfully as well.
* creating custom tools: the example shows how to filter the data for North American wildfires -- it's a useful example; I think it might be even more helpful to list some of the common sources of data and practice importing them and working with them by developing additional custom tools.
* working with attribute and spatial queries: I think it would have been good to go into a bit more detail about how / why syntax decisions are made, and to discuss the logic, the flow, and the structure; after all, mind and the mental processes are where clean code begins and ends. That said, the section discusses how Python interprets the queries and how / when it matters where a string is placed. The examples are clear, but I always need lots of examples, so I would have welcomed even more examples, but that would perhaps confuse some users, so I concluded that the book hit the right balance.
* for the more adventurous, the book includes how to use the add-in wizard. I have always been a bit leery of add-ins, believing (perhaps superstitiously) that they will create conflicts, and unleash a small troop of gremlins. This chapter shows how / where to place an add-in in a folder that is easily discoverable by ArcGIS Desktop. This is probably the key to having the thing work, and it solves a small mystery of why add-ins sometimes do not work.
In sum, I'd like to say that I find the book to be very clear, well-organized, and helpful. It's likely to have a nice, long shelf life as well.
I posted a version of this review on Amazon on the product page. Now you know I'm "Happy with Books."
