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using JuliaDB

Missing Values

Julia has several different ways of representing missing data. If a column of data may contain missing values, JuliaDB supports both missing value representations of Union{T, Missing} and DataValue{T}.

While Union{T, Missing} is the default representation, functions that generate missing values (join) have a missingtype = Missing keyword argument that can be set to DataValue.

  • The convertmissing function is used to switch the representation of missing values.
using DataValues
convertmissing(table([1, NA]), Missing)
convertmissing(table([1, missing]), DataValue)
  • The dropmissing function will remove rows that contain Missing or missing DataValues.
dropmissing(table([1, NA]))
dropmissing(table([1, missing]))