correct some compat claims

Author: Christopher Doris

README.md

@@ -44,4 +44,4 @@ The existing package [PyCall](https://github.com/JuliaPy/PyCall.jl) is another s
 - PythonCall by default never copies mutable objects when converting, but instead directly wraps the mutable object. This means that modifying the converted object modifies the original, and conversion is faster.
 - PythonCall does not usually automatically convert results to Julia values, but leaves them as Python objects. This makes it easier to do Pythonic things with these objects (e.g. accessing methods) and is type-stable.
 - PythonCall installs dependencies into a separate conda environment for each Julia project. This means each Julia project can have an isolated set of Python dependencies.
-- PythonCall supports Julia 1.0+ and Python 3.5+ whereas PyCall supports Julia 0.7+ and Python 2.7+.
+- PythonCall supports Julia 1.4+ and Python 3.5+ whereas PyCall supports Julia 0.7+ and Python 2.7+.

docs/src/pycall.md

@@ -69,4 +69,4 @@ Note also that JuliaCall will use a separate Julia project for each virtual/cond
 
 ### Compatability
 
-PyCall supports Julia 0.7+ and Python 2.7+, whereas PythonCall supports Julia 1.0+ and Python 3.5+. PyCall requires numpy to be installed, PythonCall doesn't (it provides the same fast array access through the buffer protocol and array interface).
+PyCall supports Julia 0.7+ and Python 2.7+, whereas PythonCall supports Julia 1.4+ and Python 3.5+. PyCall requires numpy to be installed, PythonCall doesn't (it provides the same fast array access through the buffer protocol and array interface).