diff --git a/NEWS.md b/NEWS.md
index 930df8b0..10378f0f 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -10,7 +10,14 @@
 
 ---
 ## (current master)
-- All new development should target Julia 0.7!
+- All new development should target Julia 1.x!
+
+## 0.19.0
+- Refactor conditional loading to use Requires
+- Many fixes for 1.0 compatibility
+
+## 0.18.0
+- update minor version to 0.7
 
 ## 0.17.4
 - fix thickness_scaling for pyplot
diff --git a/src/arg_desc.jl b/src/arg_desc.jl
index 06407929..afccd2e6 100644
--- a/src/arg_desc.jl
+++ b/src/arg_desc.jl
@@ -21,7 +21,7 @@ const _arg_desc = KW(
 :markerstrokewidth 	=> "Number. Width of the marker stroke (border. in pixels)",
 :markerstrokecolor 	=> "Color Type. Color of the marker stroke (border).  `:match` will take the value from `:foreground_color_subplot`.",
 :markerstrokealpha 	=> "Number in [0,1]. The alpha/opacity override for the marker stroke (border).  `nothing` (the default) means it will take the alpha value of markerstrokecolor.",
-:bins              	=> "Integer, NTuple{2,Integer}, AbstractVector or Symbol. Default is :auto (the Freedman-Diaconis rule). For histogram-types, defines the approximate number of bins to aim for, or the auto-binning algorithm to use (:sturges, :sqrt, :rice, :scott or :fd). For fine-grained control pass a Vector of break values, e.g. `linspace(extrema(x)..., 25)`",
+:bins              	=> "Integer, NTuple{2,Integer}, AbstractVector or Symbol. Default is :auto (the Freedman-Diaconis rule). For histogram-types, defines the approximate number of bins to aim for, or the auto-binning algorithm to use (:sturges, :sqrt, :rice, :scott or :fd). For fine-grained control pass a Vector of break values, e.g. `range(min(x), stop = extrema(x), length = 25)`",
 :smooth            	=> "Bool.  Add a regression line?",
 :group             	=> "AbstractVector. Data is split into a separate series, one for each unique value in `group`.",
 :x                 	=> "Various. Input data. First Dimension",
diff --git a/src/backends/hdf5.jl b/src/backends/hdf5.jl
index d8919942..2c6b3ecb 100644
--- a/src/backends/hdf5.jl
+++ b/src/backends/hdf5.jl
@@ -270,7 +270,7 @@ function _hdf5plot_writecount(grp, n::Int) #Write directly to group
 end
 function _hdf5plot_gwritefields(grp, k::String, v)
     grp = HDF5.g_create(grp, k)
-    for _k in fieldnames(v)
+    for _k in fieldnames(typeof(v))
         _v = getfield(v, _k)
         kstr = string(_k)
         _hdf5plot_gwrite(grp, kstr, _v)
diff --git a/src/deprecated/colors.jl b/src/deprecated/colors.jl
index 4646934a..5e01bdc1 100644
--- a/src/deprecated/colors.jl
+++ b/src/deprecated/colors.jl
@@ -120,7 +120,7 @@ struct ColorGradient <: ColorScheme
 
     # # otherwise interpolate evenly between the minval and maxval
     # minval, maxval = minimum(vals), maximum(vals)
-    # vs = Float64[interpolate(minval, maxval, w) for w in linspace(0, 1, length(cs))]
+    # vs = Float64[interpolate(minval, maxval, w) for w in range(0, stop = 1, length = length(cs))]
     # new(convertColor(cs,alpha), vs)
 
     # interpolate the colors for each value
@@ -147,7 +147,7 @@ function ColorGradient(s::Symbol, vals::AVec{T} = 0:0; kw...) where T<:Real
   ColorGradient(cs, vals; kw...)
 end
 
-# function ColorGradient{T<:Real}(cs::AVec, vals::AVec{T} = linspace(0, 1, length(cs)); kw...)
+# function ColorGradient{T<:Real}(cs::AVec, vals::AVec{T} = range(0, stop = 1, length = length(cs)); kw...)
 #   ColorGradient(map(convertColor, cs), vals; kw...)
 # end
 
diff --git a/src/recipes.jl b/src/recipes.jl
index 26796657..be27cdd4 100644
--- a/src/recipes.jl
+++ b/src/recipes.jl
@@ -284,7 +284,7 @@ end
     # where the points are the control points of the curve
     for rng in iter_segments(args...)
         length(rng) < 2 && continue
-        ts = linspace(0, 1, npoints)
+        ts = range(0, stop = 1, length = npoints)
         nanappend!(newx, map(t -> bezier_value(_cycle(x,rng), t), ts))
         nanappend!(newy, map(t -> bezier_value(_cycle(y,rng), t), ts))
         if z != nothing
@@ -498,21 +498,25 @@ function _stepbins_path(edge, weights, baseline::Real, xscale::Symbol, yscale::S
     log_scale_x = xscale in _logScales
     log_scale_y = yscale in _logScales
 
-    nbins = length(linearindices(weights))
-    if length(linearindices(edge)) != nbins + 1
+    nbins = length(eachindex(weights))
+    if length(eachindex(edge)) != nbins + 1
         error("Edge vector must be 1 longer than weight vector")
     end
 
     x = eltype(edge)[]
     y = eltype(weights)[]
 
-    it_e, it_w = start(edge), start(weights)
-    a, it_e = next(edge, it_e)
+    it_tuple_e = iterate(edge)
+    a, it_state_e = it_tuple_e
+    it_tuple_e = iterate(edge, it_state_e)
+
+    it_tuple_w = iterate(weights)
+
     last_w = eltype(weights)(NaN)
-    i = 1
-    while (!done(edge, it_e) && !done(edge, it_e))
-        b, it_e = next(edge, it_e)
-        w, it_w = next(weights, it_w)
+
+    while it_tuple_e != nothing && it_tuple_w != nothing
+        b, it_state_e = it_tuple_e
+        w, it_state_w = it_tuple_w
 
         if (log_scale_x && a ≈ 0)
             a = b/_logScaleBases[xscale]^3
@@ -536,6 +540,9 @@ function _stepbins_path(edge, weights, baseline::Real, xscale::Symbol, yscale::S
 
         a = b
         last_w = w
+
+        it_tuple_e = iterate(edge, it_state_e)
+        it_tuple_w = iterate(weights, it_state_w)
     end
     if (last_w != baseline)
         push!(x, a)
diff --git a/src/series.jl b/src/series.jl
index ff55801b..70ec5f0d 100644
--- a/src/series.jl
+++ b/src/series.jl
@@ -518,7 +518,7 @@ end
     xs, fs
 end
 @recipe f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, u::AVec) where {F<:Function,G<:Function}  = mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u)
-@recipe f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, umin::Number, umax::Number, n = 200) where {F<:Function,G<:Function} = fx, fy, linspace(umin, umax, n)
+@recipe f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, umin::Number, umax::Number, n = 200) where {F<:Function,G<:Function} = fx, fy, range(umin, stop = umax, length = n)
 
 #
 # # special handling... 3D parametric function(s)
@@ -526,7 +526,7 @@ end
     mapFuncOrFuncs(fx, u), mapFuncOrFuncs(fy, u), mapFuncOrFuncs(fz, u)
 end
 @recipe function f(fx::FuncOrFuncs{F}, fy::FuncOrFuncs{G}, fz::FuncOrFuncs{H}, umin::Number, umax::Number, numPoints = 200) where {F<:Function,G<:Function,H<:Function}
-    fx, fy, fz, linspace(umin, umax, numPoints)
+    fx, fy, fz, range(umin, stop = umax, length = numPoints)
 end
 
 #
diff --git a/src/themes.jl b/src/themes.jl
index 5d1c032f..da313498 100644
--- a/src/themes.jl
+++ b/src/themes.jl
@@ -10,7 +10,7 @@ end
 
 function _get_defaults(s::Symbol)
     thm = PlotThemes._themes[s]
-    if :defaults in fieldnames(thm)
+    if :defaults in fieldnames(typeof(thm))
         return thm.defaults
     else # old PlotTheme type
         defaults = KW(
@@ -132,7 +132,7 @@ _get_showtheme_args(thm::Symbol, func::Symbol) = thm, get(_color_functions, func
 
     f(r) = sin(r) / r
     _norm(x, y) = norm([x, y])
-    x = y = linspace(-3π, 3π, 30)
+    x = y = range(-3π, stop = 3π, length = 30)
     z = f.(_norm.(x, y'))
     wi = 2:3:30
 
@@ -152,7 +152,7 @@ _get_showtheme_args(thm::Symbol, func::Symbol) = thm, get(_color_functions, func
     end
 
     n = 100
-    ts = linspace(0, 10π, n)
+    ts = range(0, stop = 10π, length = n)
     x = ts .* cos.(ts)
     y = (0.1ts) .* sin.(ts)
     z = 1:n