Internal function for adding bins that do not contain data

binstats(df, axis_col, axis_edges, bin_col; 
    grp_function = [nrow], col_function = [mean], missing_bin = false)

Returns a DataFrame containing function values for binned variables of df.

Arguments

• axis_col: binning axes column(s)
• axis_edges: bin edges for axis_col
• bin_col: column variable(s) to be binned
• grp_function = [nrow]: column independent funciton(s) to be applied at group level
• var_function = [mean]: column dependent funciton(s) to be applied to bin_col at group level
• missing_bin = false: include missing bins

Examples

```jldoctest julia> df = DataFrame(x=sin.(0:0.01:100), y = cos.(0:0.01:100), v1 = 0:0.01:100, v2 = (0:0.01:100).^2)

bin as a function of x and return the nrow and mean of v1 within each bin. x labels are bin centers

julia> binstats(df, :x, [-1, -.5, -0.25, 1], :v1) 3×3 DataFrame Row │ x nrow v1_mean │ Float64 Int64 Float64 ─────┼───────────────────────── 1 │ -0.75 3350 51.8438 2 │ -0.375 841 50.2257 3 │ 0.375 5810 48.9042

bin as a function of x and y nd return the nrow and mean of v1 within each bin

julia> binstats(df, [:x, :y], [[-1, -.5, -0.25, 1], [-1, 0, 1]], [:v1]) 6×4 DataFrame Row │ x y nrow v1_mean │ Float64 Float64 Int64 Float64 ─────┼────────────────────────────────── 1 │ -0.75 -0.5 1676 51.3281 2 │ -0.75 0.5 1674 52.36 3 │ -0.375 -0.5 434 50.7117 4 │ -0.375 0.5 407 49.7075 5 │ 0.375 -0.5 2918 49.6149 6 │ 0.375 0.5 2891 48.2039

bin as a function of x and y and return the mean of v1 and the std of v2 within each bin

julia> binstats(df, [:x, :y], [[-1, -.5, -0.25, 1], [-1, 0, 1]], [:v1, :v2], grpfunction = [], colfunction = [mean, std]) 6×4 DataFrame Row │ x y v1mean v2std │ Float64 Float64 Float64 Float64 ─────┼──────────────────────────────────── 1 │ -0.75 -0.5 51.3281 3067.6 2 │ -0.75 0.5 52.36 3123.3 3 │ -0.375 -0.5 50.7117 3025.52 4 │ -0.375 0.5 49.7075 2790.1 5 │ 0.375 -0.5 49.6149 2970.39 6 │ 0.375 0.5 48.2039 2864.74

bin as a function of x and y and return the mean and std of both v1 and v2 within each bin

NOTE: col_function from changed Vector to Matrix, i.e. comma removed from col_function

julia> binstats(df, [:x, :y], [[-1, -.5, -0.25, 1], [-1, 0, 1]], [:v1, :v2], grpfunction = [], colfunction = [mean std]) 6×6 DataFrame Row │ x y v1mean v2mean v1std v2std │ Float64 Float64 Float64 Float64 Float64 Float64 ─────┼────────────────────────────────────────────────────── 1 │ -0.75 -0.5 51.3281 3474.45 28.9892 3067.6 2 │ -0.75 0.5 52.36 3579.9 28.9626 3123.3 3 │ -0.375 -0.5 50.7117 3407.85 28.9501 3025.52 4 │ -0.375 0.5 49.7075 3210.43 27.2289 2790.1 5 │ 0.375 -0.5 49.6149 3300.65 28.9707 2970.39 6 │ 0.375 0.5 48.2039 3149.59 28.7447 2864.74