Apply suggestions from code review

Co-Authored-By: Felicity Chapman <felicitymay@github.com>

Author: shati-patel

docs/language/learn-ql/python/introduce-libraries-python.rst

@@ -12,7 +12,7 @@ The rest of this tutorial summarizes the contents of the standard libraries for
 Overview of the library
 -----------------------
 
-The CodeQL library for Python incorporates a large number of classes. Each class corresponds either to one kind of entity in Python source code or to an entity that can be derived form the source code using static analysis. These classes can be divided into four categories:
+The CodeQL library for Python incorporates a large number of classes. Each class corresponds either to one kind of entity in Python source code or to an entity that can be derived from the source code using static analysis. These classes can be divided into four categories:
 
 -  **Syntactic** - classes that represent entities in the Python source code.
 -  **Control flow** - classes that represent entities from the control flow graphs.

docs/language/learn-ql/writing-queries/path-queries.rst

@@ -105,7 +105,7 @@ To do this you need to define a `query predicate <https://help.semmle.com/QL/ql-
 This predicate defines the edge relations of the graph you are computing, and it is used to compute the paths related to each result that your query generates. 
 You can import a predefined ``edges`` predicate from a path graph module in one of the standard data flow libraries. In addition to the path graph module, the data flow libraries contain the other ``classes``, ``predicates``, and ``modules`` that are commonly used in data flow analysis. The import statement to use depends on the language that you are analyzing.
 
-For C/C++, C#. Java, and JavaScript you would use::
+For C/C++, C#, Java, and JavaScript you would use::
 
     import DataFlow::PathGraph