Internals

The functions, methods and types listed on this page are internal to DataFrames and are not considered to be part of the public API.

# DataFrames.compacttype — Function

compacttype(T::Type, maxwidth::Int=8, initial::Bool=true)

Return compact string representation of type T.

For displaying data frame we do not want string representation of type to be longer than maxwidth. This function implements rules how type names are cropped if they are longer than maxwidth.

# DataFrames.gennames — Function

gennames(n::Integer)

Generate standardized names for columns of a DataFrame. The first name will be :x1, the second :x2, etc.

# DataFrames.getmaxwidths — Function

DataFrames.getmaxwidths(df::AbstractDataFrame,
                        io::IO,
                        rowindices1::AbstractVector{Int},
                        rowindices2::AbstractVector{Int},
                        rowlabel::Symbol,
                        rowid::Union{Integer, Nothing},
                        show_eltype::Bool,
                        buffer::IOBuffer)

Calculate, for each column of an AbstractDataFrame, the maximum string width used to render the name of that column, its type, and the longest entry in that column — among the rows of the data frame will be rendered to IO. The widths for all columns are returned as a vector.

Return a Vector{Int} giving the maximum string widths required to render each column, including that column’s name and type.

The last entry of the result vector is the string width of the implicit row ID column contained in every AbstractDataFrame.

Arguments

df::AbstractDataFrame: The data frame whose columns will be printed.
io::IO: The IO to which df is to be printed
`rowindices1::AbstractVector{Int}: A set of indices of the first chunk of the AbstractDataFrame that would be rendered to IO.
`rowindices2::AbstractVector{Int}: A set of indices of the second chunk of the AbstractDataFrame that would be rendered to IO. Can be empty if the AbstractDataFrame would be printed without any ellipses.
rowlabel::AbstractString: The label that will be used when rendered the numeric ID’s of each row. Typically, this will be set to "Row".
rowid: Used to handle showing DataFrameRow.
show_eltype: Whether to print the column type under the column name in the heading.
buffer: buffer passed around to avoid reallocations in ourstrwidth

# DataFrames.ourshow — Function

DataFrames.ourshow(io::IO, x::Any, truncstring::Int)

Render a value to an IO object compactly using print. truncstring indicates the approximate number of text characters width to truncate the output (if it is a non-positive value then no truncation is applied).

# DataFrames.ourstrwidth — Function

DataFrames.ourstrwidth(io::IO, x::Any, buffer::IOBuffer, truncstring::Int)

Determine the number of characters that would be used to print a value.

# DataFrames.@spawn_for_chunks — Macro

@spawn_for_chunks basesize for i in range ... end

Parallelize a for loop by spawning separate tasks iterating each over a chunk of at least basesize elements in range.

A number of tasks higher than Threads.nthreads() may be spawned, since that can allow for a more efficient load balancing in case some threads are busy (nested parallelism).

# DataFrames.@spawn_or_run_task — Macro

@spawn_or_run_task threads expr

Equivalent to Threads.@spawn if threads === true, otherwise run expr and return a Task that returns its value.

# DataFrames.@spawn_or_run — Macro

@spawn_or_run threads expr

Equivalent to Threads.@spawn if threads === true, otherwise run expr.

# DataFrames.default_table_transformation — Function

default_table_transformation(df_sel::AbstractDataFrame, fun)

This is a default implementation called when AsTable(...) => fun is requested. The df_sel argument is a data frame storing columns selected by AsTable(...) selector.

# DataFrames.isreadonly — Function

isreadonly(fun)

Trait returning a Bool indicator if function fun is only reading the passed argument. Such a function guarantees not to modify nor return in any form the passed argument. By default false is returned.

This function might become a part of the public API of DataFrames.jl in the future, currently it should be considered experimental. Adding a method to isreadonly for a specific function fun will improve performance of AsTable(...) => ByRow(fun∘collect) operation.