remove hist and friends from docs

base/docs/helpdb/Base.jl

@@ -287,14 +287,6 @@ Multiply elements of `A` over the singleton dimensions of `r`, and write results
 """
 prod!
 
-"""
-    hist2d!(counts, M, e1, e2) -> (e1, e2, counts)
-
-Compute a "2d histogram" with respect to the bins delimited by the edges given in `e1` and
-`e2`. This function writes the results to a pre-allocated array `counts`.
-"""
-hist2d!
-
 """
     airybi(x)
 
@@ -4291,18 +4283,6 @@ An indexing operation into an array, `a`, tried to access an out-of-bounds eleme
 """
 BoundsError
 
-"""
-    hist2d(M, e1, e2) -> (edge1, edge2, counts)
-
-Compute a "2d histogram" of a set of N points specified by N-by-2 matrix `M`. Arguments `e1`
-and `e2` are bins for each dimension, specified either as integer bin counts or vectors of
-bin edges. The result is a tuple of `edge1` (the bin edges used in the first dimension),
-`edge2` (the bin edges used in the second dimension), and `counts`, a histogram matrix of
-size `(length(edge1)-1, length(edge2)-1)`. Note: Julia does not ignore `NaN` values in the
-computation.
-"""
-hist2d
-
 """
     which(f, types)
 
@@ -5895,15 +5875,6 @@ order with arrays.
 """
 symdiff
 
-"""
-    histrange(v, n)
-
-Compute *nice* bin ranges for the edges of a histogram of `v`, using approximately `n` bins.
-The resulting step sizes will be 1, 2 or 5 multiplied by a power of 10. Note: Julia does not
-ignore `NaN` values in the computation.
-"""
-histrange
-
 """
     eta(x)
 
@@ -6886,14 +6857,6 @@ of a string. Control characters are the non-printing characters of the Latin-1 s
 """
 iscntrl
 
-"""
-    hist!(counts, v, e) -> e, counts
-
-Compute the histogram of `v`, using a vector/range `e` as the edges for the bins. This
-function writes the resultant counts to a pre-allocated array `counts`.
-"""
-hist!
-
 """
     minimum!(r, A)
 
@@ -9634,24 +9597,6 @@ transformation is performed internally to map the infinite interval to a finite
 """
 quadgk
 
-"""
-    hist(v[, n]) -> e, counts
-
-Compute the histogram of `v`, optionally using approximately `n` bins. The return values are
-a range `e`, which correspond to the edges of the bins, and `counts` containing the number
-of elements of `v` in each bin. Note: Julia does not ignore `NaN` values in the computation.
-"""
-hist(v,n::Int=?)
-
-"""
-    hist(v, e) -> e, counts
-
-Compute the histogram of `v` using a vector/range `e` as the edges for the bins. The result
-will be a vector of length `length(e) - 1`, such that the element at location `i` satisfies
-`sum(e[i] .< v .<= e[i+1])`. Note: Julia does not ignore `NaN` values in the computation.
-"""
-hist(v,e)
-
 """
     islower(c::Union{Char,AbstractString}) -> Bool
 

contrib/BBEditTextWrangler-julia.plist

@@ -496,11 +496,6 @@
             <string>hex2bytes</string>
             <string>hex2num</string>
             <string>hex</string>
-            <string>hist!</string>
-            <string>hist2d!</string>
-            <string>hist2d</string>
-            <string>hist</string>
-            <string>histrange</string>
             <string>homedir</string>
             <string>htol</string>
             <string>hton</string>

doc/stdlib/math.rst

@@ -1750,42 +1750,6 @@ Statistics
 
    Like ``median``\ , but may overwrite the input vector.
 
-.. function:: hist(v[, n]) -> e, counts
-
-   .. Docstring generated from Julia source
-
-   Compute the histogram of ``v``\ , optionally using approximately ``n`` bins. The return values are a range ``e``\ , which correspond to the edges of the bins, and ``counts`` containing the number of elements of ``v`` in each bin. Note: Julia does not ignore ``NaN`` values in the computation.
-
-.. function:: hist(v, e) -> e, counts
-
-   .. Docstring generated from Julia source
-
-   Compute the histogram of ``v`` using a vector/range ``e`` as the edges for the bins. The result will be a vector of length ``length(e) - 1``\ , such that the element at location ``i`` satisfies ``sum(e[i] .< v .<= e[i+1])``\ . Note: Julia does not ignore ``NaN`` values in the computation.
-
-.. function:: hist!(counts, v, e) -> e, counts
-
-   .. Docstring generated from Julia source
-
-   Compute the histogram of ``v``\ , using a vector/range ``e`` as the edges for the bins. This function writes the resultant counts to a pre-allocated array ``counts``\ .
-
-.. function:: hist2d(M, e1, e2) -> (edge1, edge2, counts)
-
-   .. Docstring generated from Julia source
-
-   Compute a "2d histogram" of a set of N points specified by N-by-2 matrix ``M``\ . Arguments ``e1`` and ``e2`` are bins for each dimension, specified either as integer bin counts or vectors of bin edges. The result is a tuple of ``edge1`` (the bin edges used in the first dimension), ``edge2`` (the bin edges used in the second dimension), and ``counts``\ , a histogram matrix of size ``(length(edge1)-1, length(edge2)-1)``\ . Note: Julia does not ignore ``NaN`` values in the computation.
-
-.. function:: hist2d!(counts, M, e1, e2) -> (e1, e2, counts)
-
-   .. Docstring generated from Julia source
-
-   Compute a "2d histogram" with respect to the bins delimited by the edges given in ``e1`` and ``e2``\ . This function writes the results to a pre-allocated array ``counts``\ .
-
-.. function:: histrange(v, n)
-
-   .. Docstring generated from Julia source
-
-   Compute *nice* bin ranges for the edges of a histogram of ``v``\ , using approximately ``n`` bins. The resulting step sizes will be 1, 2 or 5 multiplied by a power of 10. Note: Julia does not ignore ``NaN`` values in the computation.
-
 .. function:: midpoints(e)
 
    .. Docstring generated from Julia source