Analyzing and Visualizing Data with F#

Chapter 1. Accessing Data with Type Providers

Working with data was not always as easy as nowadays. For example, processing the data from the decennial 1880 US Census took eight years. For the 1890 census, the United States Census Bureau hired Herman Hollerith, who invented a number of devices to automate the process. A pantograph punch was used to punch the data on punch cards, which were then fed to the tabulator that counted cards with certain properties, or to the sorter for filtering. The census still required a large amount of clerical work, but Hollerith’s machines sped up the process eight times to just one year.¹

These days, filtering and calculating sums over hundreds of millions of rows (the number of forms received in the 2010 US Census) can take seconds. Much of the data from the US Census, various Open Government Data initiatives, and from international organizations like the World Bank is available online and can be analyzed by anyone. Hollerith’s tabulator and sorter have become standard library functions in many programming languages and data analytics libraries.

Making data analytics easier no longer involves building new physical devices, but instead involves creating better software tools and programming languages. So, let’s see how the F# language and its unique features like type providers make the task of modern data analysis even easier!

Data Science Workflow

Data science is an umbrella term for a wide range of fields and disciplines that are needed to ...