DOC: Some rewording and typos.

CHANGELOG.md

@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Changed ###
 
 - The `TableImporter` and its subclasses now change all integer datatypes to the
-  nullable `pandas.Int64Datatype` s.th. integer columns with empty fields can be
+  nullable `pandas.Int64Datatype` so that integer columns with empty fields can be
   treated properly. In case you don't want the datatypes to be changed
   automatically, initialize the `TableImporter` with
   `convert_int_to_nullable_int=False`.

src/caosadvancedtools/table_importer.py

@@ -244,8 +244,8 @@ class TableImporter():
         Parameters
         ----------
         converters : dict
-          Dict with column names as keys and converter functions as values. This dict also defines
-          what columns are required to exist throught the existing keys. The converter functions are
+          Dict with column names as keys and converter functions as values. This dict's keys also
+          define what columns must exist. The converter functions are
           applied to the cell values. They should also check for ValueErrors, such that a separate
           value check is not necessary.
 
@@ -267,7 +267,7 @@ class TableImporter():
         convert_int_to_nullable_int : bool, optional
           Whether to convert all integer datatypes to ``pandas.Int64Dtype()``
           which is nullable, to allow for integer columns with empty fields. If
-          set to False, a ``DataInConsistencyError`` will be raised in case of
+          set to False, a ``DataInconsistencyError`` will be raised in case of
           empty fields in integer columns.  Default is True.
         """
 

unittests/test_table_importer.py

@@ -370,7 +370,7 @@ class CSVImporterTest(TableImporterTest):
             df = importer_strict.read_file(tmpfile.name)
         assert "Integer column has NA values in column 1" in str(die.value)
 
-        # ... except when a nullable datatype is set explicitly
+        # ... except when a nullable datatype is set manually beforehand
         kwargs["datatypes"]["int_with_gaps"] = "Int64"
         importer_strict = CSVImporter(convert_int_to_nullable_int=False, **kwargs)
         df = importer_strict.read_file(tmpfile.name)