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add cols to describe #2020

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Nov 26, 2019
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add cols to describe #2020

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add cols to describe
bkamins Nov 19, 2019
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bkamins Nov 20, 2019
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76 changes: 64 additions & 12 deletions src/abstractdataframe/abstractdataframe.jl
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Expand Up @@ -241,8 +241,8 @@ Base.last(df::AbstractDataFrame, n::Integer) = df[max(1,nrow(df)-n+1):nrow(df),


"""
describe(df::AbstractDataFrame)
describe(df::AbstractDataFrame, stats::Union{Symbol, Pair{<:Symbol}}...)
describe(df::AbstractDataFrame; cols=:)
describe(df::AbstractDataFrame, stats::Union{Symbol, Pair{<:Symbol}}...; cols=:)

Return descriptive statistics for a data frame as a new `DataFrame`
where each row represents a variable and each column a summary statistic.
Expand All @@ -258,6 +258,8 @@ where each row represents a variable and each column a summary statistic.
- `:all` as the only `Symbol` argument to return all statistics.
- A `name => function` pair where `name` is a `Symbol`. This will create
a column of summary statistics with the provided name.
- `cols` : a keyword argument allowing to select only a subset of columns from `df`
to describe; all standard column selection methods are allowed
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# Details
For `Real` columns, compute the mean, standard deviation, minimum, first quantile, median,
Expand All @@ -279,22 +281,72 @@ to each column as the only argument. For columns allowing for missing values,
the vector is wrapped in a call to [`skipmissing`](@ref): custom functions must therefore
support such objects (and not only vectors), and cannot access missing values.

For consistency with DataAPI.jl an `io` argument can be passed to `describe` in
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Shouldn't we just drop this (in another PR)? Clearly if you pass io you expect the result to be printed there, so it's actively misleading not to throw an error. Or the method taking io should call show(io, describe(...)).

Anyway when moving things from StatsBase to Statistics I'd like to change that API so that describe always returns a special object that can be printed, instead of printing the result directly. That's more useful and more standard.

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100% agreed in all you write - passing io made no sense to me here, but it was defined in DataAPI.jl and I did not want to make breaking changes in this PR.

So - after merging this PR do we make another PR that deprecates io? (this is what I would do in DataFrames.jl; all other actions are needed in other packages, but they can be done independently, as we clearly document how describe with AbstractDataFrame works).

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Right, I think we can start changing this in DataFrames, the StatsBase to Statistics move will take longer.

a first position but it is currently ignored.

# Examples
```julia
df = DataFrame(i = 1:10, x = rand(10), y = rand(["a", "b", "c"], 10))
describe([io,] df)
describe([io,] df, :all)
describe([io,] df, :min, :max)
describe([io,] df, :min, :sum => sum)
julia> df = DataFrame(i=1:10, x=0.1:0.1:1.0, y='a':'j')
10×3 DataFrame
│ Row │ i │ x │ y │
│ │ Int64 │ Float64 │ Char │
├─────┼───────┼─────────┼──────┤
│ 1 │ 1 │ 0.1 │ 'a' │
│ 2 │ 2 │ 0.2 │ 'b' │
│ 3 │ 3 │ 0.3 │ 'c' │
│ 4 │ 4 │ 0.4 │ 'd' │
│ 5 │ 5 │ 0.5 │ 'e' │
│ 6 │ 6 │ 0.6 │ 'f' │
│ 7 │ 7 │ 0.7 │ 'g' │
│ 8 │ 8 │ 0.8 │ 'h' │
│ 9 │ 9 │ 0.9 │ 'i' │
│ 10 │ 10 │ 1.0 │ 'j' │

julia> describe(df)
3×8 DataFrame
│ Row │ variable │ mean │ min │ median │ max │ nunique │ nmissing │ eltype │
│ │ Symbol │ Union… │ Any │ Union… │ Any │ Union… │ Nothing │ DataType │
├─────┼──────────┼────────┼─────┼────────┼─────┼─────────┼──────────┼──────────┤
│ 1 │ i │ 5.5 │ 1 │ 5.5 │ 10 │ │ │ Int64 │
│ 2 │ x │ 0.55 │ 0.1 │ 0.55 │ 1.0 │ │ │ Float64 │
│ 3 │ y │ │ 'a' │ │ 'j' │ 10 │ │ Char │

julia> describe(df, :min, :max)
3×3 DataFrame
│ Row │ variable │ min │ max │
│ │ Symbol │ Any │ Any │
├─────┼──────────┼─────┼─────┤
│ 1 │ i │ 1 │ 10 │
│ 2 │ x │ 0.1 │ 1.0 │
│ 3 │ y │ 'a' │ 'j' │

julia> describe(df, :min, :sum => sum)
3×3 DataFrame
│ Row │ variable │ min │ sum │
│ │ Symbol │ Any │ Any │
├─────┼──────────┼─────┼─────┤
│ 1 │ i │ 1 │ 55 │
│ 2 │ x │ 0.1 │ 5.5 │
│ 3 │ y │ 'a' │ │

julia> describe(df, :min, :sum => sum, cols=:x)
1×3 DataFrame
│ Row │ variable │ min │ sum │
│ │ Symbol │ Float64 │ Float64 │
├─────┼──────────┼─────────┼─────────┤
│ 1 │ x │ 0.1 │ 5.5 │
```
"""
DataAPI.describe(io::IO, df::AbstractDataFrame, stats::Union{Symbol, Pair{Symbol}}...) =
_describe(df, collect(stats))
DataAPI.describe(io::IO, df::AbstractDataFrame, stats::Union{Symbol, Pair{Symbol}}...;
cols=:) =
_describe(select(df, cols, copycols=false), collect(stats))

DataAPI.describe(io::IO, df::AbstractDataFrame) =
_describe(df, [:mean, :min, :median, :max, :nunique, :nmissing, :eltype])
DataAPI.describe(io::IO, df::AbstractDataFrame; cols=:) =
_describe(select(df, cols, copycols=false),
[:mean, :min, :median, :max, :nunique, :nmissing, :eltype])

DataAPI.describe(df::AbstractDataFrame, stats::Union{Symbol, Pair{Symbol}}...) = DataAPI.describe(stdout, df, stats...)
DataAPI.describe(df::AbstractDataFrame, stats::Union{Symbol, Pair{Symbol}}...; cols=:) =
DataAPI.describe(stdout, df, stats...; cols=cols)

function _describe(df::AbstractDataFrame, stats::AbstractVector)
predefined_funs = Symbol[s for s in stats if s isa Symbol]
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3 changes: 3 additions & 0 deletions test/dataframe.jl
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Expand Up @@ -1029,6 +1029,9 @@ end
@test describe(df, :mean) ≅ DataFrame(variable = [:a, :b, :c],
mean = [NaN, nothing, nothing])

@test describe(df, :all, cols=Not(1)) ≅ describe(select(df, Not(1)), :all)
@test describe(df, cols=Not(1)) ≅ describe(select(df, Not(1)))

@test_throws ArgumentError describe(df, :mean, :all)
end

Expand Down