From 7787203ed6f072f0678bca40a29363f6c4f00d02 Mon Sep 17 00:00:00 2001
From: Daniel <d.hornung@indiscale.com>
Date: Fri, 28 Jun 2024 12:00:20 +0200
Subject: [PATCH] DOC: Some rewording and typos.
---
CHANGELOG.md | 2 +-
src/caosadvancedtools/table_importer.py | 6 +++---
unittests/test_table_importer.py | 2 +-
3 files changed, 5 insertions(+), 5 deletions(-)
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 33381f3c..25772147 100644
--- a/CHANGELOG.md
+++ b/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`.
diff --git a/src/caosadvancedtools/table_importer.py b/src/caosadvancedtools/table_importer.py
index 72c7ddd4..5efd0500 100755
--- a/src/caosadvancedtools/table_importer.py
+++ b/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.
"""
diff --git a/unittests/test_table_importer.py b/unittests/test_table_importer.py
index 92d79334..6d445056 100644
--- a/unittests/test_table_importer.py
+++ b/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)
--
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