Transcription of Reshaping data with the reshape package
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Reshaping data with the reshape package
Reshaping data with thereshapepackageHadley 2006 Contents1 Introduction22 Conceptual framework33 Melting Melting data with id variables encoded in column names .. Melting arrays .. Missing values in molten data .. 64 Casting molten Basic use .. Aggregation .. Margins .. Returning multiple values .. High-dimensional arrays .. Lists .. 185 Other convenience Factors .. data frames .. Miscellaneous .. 216 Case Investigating balance .. Tables of means .. Investigating inter-rep reliability .. 247 Where to go next2511 IntroductionReshaping data is a common task in practical data analysis, and it is usually tedious and often has multiple levels of grouping (nested treatments, split plot designs, or repeatedmeasurements) and typically requires investigation at multiple levels.
1 Introduction Reshaping data is a common task in practical data analysis, and it is usually tedious and unintuitive. Data often has multiple levels of grouping (nested treatments, split plot designs, or repeated
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