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sjmisc: Data and Variable Transformation Functions

Daniel Lüdecke

New functions

  • has_na() to check if variables or observations in a data frame contain NA, NaN or Inf values. Convenient shortcuts for this function are complete_cases(), incomplete_cases(), complete_vars() and incomplete_vars().
  • total_mean() to compute the overall mean of all values from all columns in a data frame.
  • prcn() to convert numeric scalars between 0 and 1 into a character-percentage value.
  • numeric_to_factor() to convert numeric variables into factors, using associated value labels as factor levels.

Changes to functions

  • set_na() now also replaces different values per variable into NA.
  • Changed behaviour of row_sums() and missing values. row_sums() gets a n-argument and now computes row sums if a row has at least n non-missing values.

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