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Published byPenelope Telfair Modified over 2 years ago

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Gold Rush Mining Public Library Data with R and Excel

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3 free online data sources We used IMLS

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The friendliest are CSV (comma sep) and XLS We downloaded a CSV

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Choose your tools wisely.

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Get a preliminary overview of your data Cleaning

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Is a powerful tool for statistical analysis.

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View(), Fix() Measures of central tendency Other calculations: sum() columns to find out which locale has highest number of internet computers, relative to registered borrowers, and reference transactions

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From 2008-2011: Which libraries have the highest percentage of hourly employed ALA MLS librarians? How many libraries have no ALA MLS librarians?

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Identify relevant columns Total staff hours ALA MLS hours Do calculations %of total staff hours are ALA MLS

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Stages of Analysis. Explore by basic stats Minimum % of staff hours Maximum % of total staff hours Average % of total staff hours

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Identify interesting data points Leads to more specific questions: Type of area? Name of library?

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2008 2009

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Beginner coder? We are Librarians. Use tools you know.

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Convert to CSV or other friendly format. For analysis: -Excel -Weka -SPSS

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Many Eyes Visual.ly

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Kusturie Moodley @KusturieM Sarah Bratt @SarahsBratt

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