diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 936f502..63c4b1b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -31,10 +31,12 @@ repos:
       - id: trailing-whitespace
       - id: end-of-file-fixer
       - id: check-yaml
+      - id: check-xml
       - id: mixed-line-ending
         args: ["--fix=lf"]
       - id: check-added-large-files
       - id: check-ast
+      - id: check-builtin-literals
       - id: check-case-conflict
       - id: check-docstring-first
       - id: check-merge-conflict
@@ -42,21 +44,53 @@ repos:
       - id: debug-statements
       - id: fix-byte-order-marker
       - id: forbid-new-submodules
+      - id: forbid-submodules
+      - id: detect-private-key
+      - id: no-commit-to-branch
+        args: ["--branch=main", "--branch=develop"]
 
-  - repo: https://github.com/asottile/pyupgrade
-    rev: v3.3.1
+  - repo: https://github.com/pre-commit/pygrep-hooks
+    rev: v1.10.0
     hooks:
-      - id: pyupgrade
+      - id: python-use-type-annotations
+      - id: python-check-blanket-noqa
+      - id: python-check-mock-methods
+      - id: python-no-eval
+      - id: python-no-log-warn
+      - id: python-use-type-annotations
+      - id: text-unicode-replacement-char
+
+  - repo: https://github.com/PyCQA/docformatter
+    rev: v1.5.1
+    hooks:
+      - id: docformatter
+
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.6.1
+    hooks:
+      - id: nbqa-check-ast
+      - id: nbqa-mypy
+        args: ["--config-file=pyproject.toml"]
+      - id: nbqa-pyupgrade
 
   - repo: https://github.com/bwhmather/ssort
     rev: v0.11.6
     hooks:
       - id: ssort
 
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v3.3.1
+    hooks:
+      - id: pyupgrade
+
   - repo: https://github.com/psf/black
     rev: 22.12.0
     hooks:
       - id: black
+        args: ["--config=pyproject.toml"]
+      - id: black-jupyter
+        args: ["--config=pyproject.toml"]
+        files: \.ipynb$
 
   - repo: https://github.com/PyCQA/isort
     rev: 5.11.4
@@ -65,7 +99,7 @@ repos:
         args: ["--profile=black"]
 
   - repo: https://github.com/PyCQA/pylint
-    rev: v2.15.9
+    rev: v2.15.10
     hooks:
       - id: pylint
         args: ["--rcfile=pyproject.toml"]
@@ -86,6 +120,11 @@ repos:
         args:
           - "-r"
 
+  - repo: https://github.com/kynan/nbstripout
+    rev: 0.6.1
+    hooks:
+      - id: nbstripout
+
   - repo: https://github.com/python-poetry/poetry
     rev: 1.3.0
     hooks:
diff --git a/src/sk_transformers/base_transformer.py b/src/sk_transformers/base_transformer.py
index cc07c59..8c3291b 100644
--- a/src/sk_transformers/base_transformer.py
+++ b/src/sk_transformers/base_transformer.py
@@ -4,11 +4,14 @@
 
 
 class BaseTransformer(BaseEstimator, TransformerMixin):
-    """
-    Base class for all custom transformers. This class inherits from BaseEstimator and TransformerMixin.
-    Its main purpose is to provide an implementation of the `fit` method that does nothing except setting the `self.fitted_` to `True`.
-    Since most custom transformers do not need to implement a fit method, this class
-    can be used as a base class for all transformers not needing a `fit` method.
+    """Base class for all custom transformers.
+
+    This class inherits from BaseEstimator and TransformerMixin. Its
+    main purpose is to provide an implementation of the `fit` method
+    that does nothing except setting the `self.fitted_` to `True`. Since
+    most custom transformers do not need to implement a fit method, this
+    class can be used as a base class for all transformers not needing a
+    `fit` method.
     """
 
     def __init__(self) -> None:
diff --git a/src/sk_transformers/datetime_transformer.py b/src/sk_transformers/datetime_transformer.py
index e09d050..a2af5d3 100644
--- a/src/sk_transformers/datetime_transformer.py
+++ b/src/sk_transformers/datetime_transformer.py
@@ -8,8 +8,7 @@
 
 
 class DurationCalculatorTransformer(BaseTransformer):
-    """
-    Calculates the duration between to given dates.
+    """Calculates the duration between to given dates.
 
     Example:
     ```python
@@ -50,8 +49,7 @@ def __init__(
         self.new_column_name = new_column_name
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transform method that calculates the duration between two dates.
+        """Transform method that calculates the duration between two dates.
 
         Args:
             X (pandas.DataFrame): The input DataFrame.
@@ -75,8 +73,8 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class TimestampTransformer(BaseTransformer):
-    """
-    Transforms a date column with a specified format into a timestamp column.
+    """Transforms a date column with a specified format into a timestamp
+    column.
 
     Example:
     ```python
@@ -109,8 +107,7 @@ def __init__(
         self.date_format = date_format
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transforms columns from the provided dataframe.
+        """Transforms columns from the provided dataframe.
 
         Args:
             X (pandas.DataFrame): Dataframe with columns to transform.
diff --git a/src/sk_transformers/deep_transformer.py b/src/sk_transformers/deep_transformer.py
index c0904a1..b2ef113 100644
--- a/src/sk_transformers/deep_transformer.py
+++ b/src/sk_transformers/deep_transformer.py
@@ -12,9 +12,12 @@
 
 
 class ToVecTransformer(BaseEstimator, TransformerMixin):
-    """
-    This transformer trains an [FT-Transformer](https://paperswithcode.com/method/ft-transformer)
-    using the [pytorch-widedeep package](https://github.com/jrzaurin/pytorch-widedeep) and extracts the embeddings
+    """This transformer trains an [FT-
+    Transformer](https://paperswithcode.com/method/ft-transformer) using the.
+
+    [pytorch-widedeep package](https://github.com/jrzaurin/pytorch-widedeep)
+    and extracts the embeddings.
+
     from its embedding layer. The output shape of the transformer is (number of rows,(`input_dim` * number of columns)).
     Please refer to [this example](https://pytorch-widedeep.readthedocs.io/en/latest/examples/09_extracting_embeddings.html)
     for pytorch_widedeep example on how to extract embeddings.
@@ -99,8 +102,8 @@ def __init__(
         self.tab_vec_: Optional[Tab2Vec] = None
 
     def fit(self, X: pd.DataFrame, y: NDArray) -> "ToVecTransformer":
-        """
-        Fits the `ToVecTransformer`. The `TabPreprocessor` is fitted and the `FTTransformer` is trained.
+        """Fits the `ToVecTransformer`. The `TabPreprocessor` is fitted and the
+        `FTTransformer` is trained.
 
         Args:
             X (pd.DataFrame): The input data.
@@ -151,8 +154,8 @@ def fit(self, X: pd.DataFrame, y: NDArray) -> "ToVecTransformer":
         return self
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transforms the input data and returns the embeddings.
+        """Transforms the input data and returns the embeddings.
+
         The output shape is (number of rows,(`input_dim` * number of columns)).
 
         Args:
diff --git a/src/sk_transformers/encoder_transformer.py b/src/sk_transformers/encoder_transformer.py
index 651996a..c9b2486 100644
--- a/src/sk_transformers/encoder_transformer.py
+++ b/src/sk_transformers/encoder_transformer.py
@@ -6,8 +6,8 @@
 
 
 class MeanEncoderTransformer(BaseEstimator, TransformerMixin):
-    """
-    Scikit-learn API for the [feature-engine MeanEncoder](https://feature-engine.readthedocs.io/en/latest/api_doc/encoding/MeanEncoder.html).
+    """Scikit-learn API for the [feature-engine MeanEncoder](https://feature-
+    engine.readthedocs.io/en/latest/api_doc/encoding/MeanEncoder.html).
 
     Example:
     ```python
@@ -44,8 +44,7 @@ def __init__(self, fill_na_value: Union[int, float] = -999) -> None:
         self.fill_na_value = fill_na_value
 
     def fit(self, X: pd.DataFrame, y: pd.Series) -> "MeanEncoderTransformer":
-        """
-        Fit the MeanEncoder to the data.
+        """Fit the MeanEncoder to the data.
 
         Args:
             X (pandas.DataFrame): DataFrame to fit the MeanEncoder to.
@@ -58,8 +57,7 @@ def fit(self, X: pd.DataFrame, y: pd.Series) -> "MeanEncoderTransformer":
         return self
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transform the data using the fitted MeanEncoder.
+        """Transform the data using the fitted MeanEncoder.
 
         Args:
             X (pandas.DataFrame): DataFrame to transform.
diff --git a/src/sk_transformers/generic_transformer.py b/src/sk_transformers/generic_transformer.py
index e92fba6..29f2cdf 100644
--- a/src/sk_transformers/generic_transformer.py
+++ b/src/sk_transformers/generic_transformer.py
@@ -10,8 +10,7 @@
 
 
 class DtypeTransformer(BaseTransformer):
-    """
-    Transformer that converts a column to a different dtype.
+    """Transformer that converts a column to a different dtype.
 
     Example:
     ```python
@@ -38,8 +37,8 @@ def __init__(self, features: List[Tuple[str, Union[str, type]]]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transform the dataframe by converting the columns to the specified dtypes.
+        """Transform the dataframe by converting the columns to the specified
+        dtypes.
 
         Args:
             X (pandas.DataFrame): dataframe to transform.
@@ -55,10 +54,12 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class AggregateTransformer(BaseTransformer):
-    """
-    This transformer uses Pandas `groupby` method and `aggregate` to apply function on a column grouped by another column.
-    Read more about Pandas [`aggregate`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.aggregate.html) method
-    to understand how to use function for aggregation. Other than Pandas function this transformer only support functions and string-names.
+    """This transformer uses Pandas `groupby` method and `aggregate` to apply
+    function on a column grouped by another column. Read more about Pandas [`ag
+    gregate`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.agg
+    regate.html) method to understand how to use function for aggregation.
+    Other than Pandas function this transformer only support functions and
+    string-names.
 
     Example:
     ```python
@@ -101,8 +102,8 @@ def __init__(self, features: List[Tuple[str, str, List[str]]]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Creates new columns by using Pandas `groupby` method and `aggregate` to apply function on the column.
+        """Creates new columns by using Pandas `groupby` method and `aggregate`
+        to apply function on the column.
 
         Args:
             X (pd.DataFrame): Input dataframe.
@@ -142,10 +143,14 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class FunctionsTransformer(BaseTransformer):
-    """
-    This transformer is a plain wrapper around the [`sklearn.preprocessing.FunctionTransformer`](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html).
-    Its main function is to apply multiple functions to different columns. Other than the scikit-learn transformer,
-    this transformer *does not* support the `inverse_func`, `accept_sparse`, `feature_names_out` and, `inv_kw_args` parameters.
+    """This transformer is a plain wrapper around the.
+
+    [`sklearn.preprocessing.FunctionTransformer`](https://scikit-learn.org/stab
+    le/modules/generated/sklearn.preprocessing.FunctionTransformer.html). Its
+    main function is to apply multiple functions to different columns. Other
+    than the scikit-learn transformer, this transformer *does not* support the
+    `inverse_func`, `accept_sparse`, `feature_names_out` and, `inv_kw_args`
+    parameters.
 
     Example:
     ```python
@@ -177,8 +182,8 @@ def __init__(
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Applies the functions to the columns, and returns the dataframe with the modified columns.
+        """Applies the functions to the columns, and returns the dataframe with
+        the modified columns.
 
         Args:
             X (pandas.DataFrame): DataFrame containing the columns to apply the functions on.
@@ -198,9 +203,10 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class MapTransformer(BaseTransformer):
-    """
-    This transformer iterates over all columns in the `features` list and applies the given callback to the column.
-    For this it uses the [`pandas.Series.map`](https://pandas.pydata.org/docs/reference/api/pandas.Series.map.html) method.
+    """This transformer iterates over all columns in the `features` list and
+    applies the given callback to the column. For this it uses the [`pandas.Ser
+    ies.map`](https://pandas.pydata.org/docs/reference/api/pandas.Series.map.ht
+    ml) method.
 
     Example:
     ```python
@@ -228,8 +234,7 @@ def __init__(self, features: List[Tuple[str, Callable]]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Applies the callback to the column.
+        """Applies the callback to the column.
 
         Args:
             X (pandas.DataFrame): Dataframe containing the the columns to apply the callback on.
@@ -248,8 +253,7 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class ColumnDropperTransformer(BaseTransformer):
-    """
-    Drops columns from a dataframe using Pandas `drop` method.
+    """Drops columns from a dataframe using Pandas `drop` method.
 
     Example:
     ```python
@@ -276,8 +280,7 @@ def __init__(self, columns: Union[str, List[str]]) -> None:
         self.columns = columns
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Returns the dataframe with the `columns` dropped.
+        """Returns the dataframe with the `columns` dropped.
 
         Args:
             X (pd.DataFrame): Dataframe to drop columns from.
@@ -290,8 +293,9 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class NaNTransformer(BaseTransformer):
-    """
-    Replace NaN values with a specified value. Internally Pandas [`fillna`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.fillna.html) method is used.
+    """Replace NaN values with a specified value. Internally Pandas [`fillna`](
+    https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.fillna.html)
+    method is used.
 
     Example:
     ```python
@@ -319,8 +323,7 @@ def __init__(self, features: List[Tuple[str, Any]]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Replace NaN values with a specified value.
+        """Replace NaN values with a specified value.
 
         Args:
             X (pandas.DataFrame): Dataframe to transform.
@@ -338,12 +341,12 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class ValueIndicatorTransformer(BaseTransformer):
-    """
-    Adds a column to a dataframe indicating if a value is equal to a specified value.
-    The idea behind this method is, that it is often useful to know if a `NaN` value was
-    present in the original data and has been changed by some imputation step.
-    Sometimes the present of a `NaN` value is actually important information.
-    But obviously this method works with any kind of data.
+    """Adds a column to a dataframe indicating if a value is equal to a
+    specified value. The idea behind this method is, that it is often useful to
+    know if a `NaN` value was present in the original data and has been changed
+    by some imputation step. Sometimes the present of a `NaN` value is actually
+    important information. But obviously this method works with any kind of
+    data.
 
     `NaN`, `None` or `np.nan` are **Not** caught by this implementation.
 
@@ -374,8 +377,8 @@ def __init__(self, features: List[Tuple[str, Any]], as_int: bool = False) -> Non
         self.as_int = as_int
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Add a column to a dataframe indicating if a value is equal to a specified value.
+        """Add a column to a dataframe indicating if a value is equal to a
+        specified value.
 
         Args:
             X (pandas.DataFrame): Dataframe to transform.
@@ -399,12 +402,12 @@ def transform(self, X: pd.DataFrame) -> pd.DataFrame:
 
 
 class QueryTransformer(BaseTransformer):
-    """
-    Applies a list of queries to a dataframe.
-    If it operates on a dataset used for supervised learning this transformer should
-    be applied on the dataframe containing `X` and `y`. So removing of columns by queries
-    also removes the corresponding `y` value.
-    Read more about queries [here](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.query.html).
+    """Applies a list of queries to a dataframe. If it operates on a dataset
+    used for supervised learning this transformer should be applied on the
+    dataframe containing `X` and `y`. So removing of columns by queries also
+    removes the corresponding `y` value. Read more about queries [here](https:/
+
+    /pandas.pydata.org/docs/reference/api/pandas.DataFrame.query.html).
 
     Example:
     ```python
@@ -432,8 +435,7 @@ def __init__(self, queries: List[str]) -> None:
         self.queries = queries
 
     def transform(self, Xy: pd.DataFrame) -> pd.DataFrame:
-        """
-        Applies the list of queries to the dataframe.
+        """Applies the list of queries to the dataframe.
 
         Args:
             Xy (pd.DataFrame): Dataframe to apply the queries to. For also operating on the target column `y` - if needed.
@@ -450,11 +452,13 @@ def transform(self, Xy: pd.DataFrame) -> pd.DataFrame:
 
 
 class ValueReplacerTransformer(BaseTransformer):
-    r"""
-    Uses Pandas `replace` method to replace values in a column. This transformer loops over the `features` and applies
-    `replace` to the according columns. If the column is not from type string but a valid regular expression is provided
-    the column will be temporarily changed to a string column and after the manipulation by `replace` changed back to its
-    original type. It may happen, that this type changing fails if the modified column is not compatible with its original type.
+    r"""Uses Pandas `replace` method to replace values in a column. This
+    transformer loops over the `features` and applies `replace` to the
+    according columns. If the column is not from type string but a valid
+    regular expression is provided the column will be temporarily changed to a
+    string column and after the manipulation by `replace` changed back to its
+    original type. It may happen, that this type changing fails if the modified
+    column is not compatible with its original type.
 
     Example:
     ```python
@@ -496,8 +500,7 @@ def __init__(self, features: List[Tuple[List[str], Any, Any]]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Replaces a value or regular expression with another value.
+        """Replaces a value or regular expression with another value.
 
         Args:
             X (pd.DataFrame): Dataframe containing the columns where values should be replaced.
@@ -538,10 +541,10 @@ def __check_for_regex(value: Any) -> bool:
 
 
 class LeftJoinTransformer(BaseTransformer):
-    """
-    Performs a database-style left-join using `pd.merge`. This transformer is suitable for
-    replacing values in a column of a dataframe by looking-up another `pd.DataFrame`
-    or `pd.Series`. Note that, the join is based on the index of the right dataframe.
+    """Performs a database-style left-join using `pd.merge`. This transformer
+    is suitable for replacing values in a column of a dataframe by looking-up
+    another `pd.DataFrame` or `pd.Series`. Note that, the join is based on the
+    index of the right dataframe.
 
     Example:
     ```python
@@ -575,8 +578,8 @@ def __init__(
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Perform a left-join on the given columns of a dataframe with another cooresponding dataframe.
+        """Perform a left-join on the given columns of a dataframe with another
+        cooresponding dataframe.
 
         Args:
             X (pd.DataFrame): Dataframe containing the columns to be joined on.
diff --git a/src/sk_transformers/number_transformer.py b/src/sk_transformers/number_transformer.py
index 77e0cf0..70d2e2d 100644
--- a/src/sk_transformers/number_transformer.py
+++ b/src/sk_transformers/number_transformer.py
@@ -10,9 +10,14 @@
 
 
 class MathExpressionTransformer(BaseTransformer):
-    """
-    Applies an function/operation to a column and a given value or column.
-    The operation can be a function from NumPy's [mathematical functions](https://numpy.org/doc/stable/reference/routines.math.html#mathematical-functions)  or [`operator`](https://docs.python.org/3/library/operator.html#module-operator) package.
+    """Applies an function/operation to a column and a given value or column.
+    The operation can be a function from NumPy's [mathematical
+    functions](https.
+
+    ://numpy.org/doc/stable/reference/routines.math.html#mathematical-
+    functions)  or
+    [`operator`](https://docs.python.org/3/library/operator.html#module-
+    operator) package.
 
     **Warning!** Some functions/operators may not work as expected. Especially not all NumPy methods are supported. For example:
     various NumPy methods return values which are not fitting the size of the source column.
@@ -73,8 +78,7 @@ def __verify_operation(self, operation: str) -> Tuple[bool, Any]:
         return is_np_op, op
 
     def __abbreviate_numpy_in_operation(self, operation: str) -> str:
-        """
-        Replaces `numpy` at the start of a string with `np`.
+        """Replaces `numpy` at the start of a string with `np`.
 
         Args:
             operation (str): The operation as a string.
@@ -88,8 +92,7 @@ def __abbreviate_numpy_in_operation(self, operation: str) -> str:
         return operation
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Applies the operation to the column and the value.
+        """Applies the operation to the column and the value.
 
         Args:
             X (pandas.DataFrame): DataFrame containing the columns to apply the operation on.
diff --git a/src/sk_transformers/string_transformer.py b/src/sk_transformers/string_transformer.py
index 8ca1b6a..abf8654 100644
--- a/src/sk_transformers/string_transformer.py
+++ b/src/sk_transformers/string_transformer.py
@@ -15,10 +15,10 @@
 
 
 class IPAddressEncoderTransformer(BaseTransformer):
-    """
-    Encodes IPv4 and IPv6 strings addresses to a float representation.
-    To shrink the values to a reasonable size IPv4 addresses are divided by 2^10 and IPv6 addresses are divided by 2^48.
-    Those values can be changed using the `ip4_divisor` and `ip6_divisor` parameters.
+    """Encodes IPv4 and IPv6 strings addresses to a float representation. To
+    shrink the values to a reasonable size IPv4 addresses are divided by 2^10
+    and IPv6 addresses are divided by 2^48. Those values can be changed using
+    the `ip4_divisor` and `ip6_divisor` parameters.
 
     Example:
     ```python
@@ -56,8 +56,7 @@ def __init__(
         self.error_value = error_value
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transforms the column containing the IP addresses to float column.
+        """Transforms the column containing the IP addresses to float column.
 
         Args:
             X (pandas.DataFrame): DataFrame to transform.
@@ -96,8 +95,7 @@ def __to_float(
 
 
 class EmailTransformer(BaseTransformer):
-    """
-    Transforms an email address into multiple features.
+    """Transforms an email address into multiple features.
 
     Example:
     ```python
@@ -125,8 +123,8 @@ def __init__(self, features: List[str]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Transforms the one column from X, containing the email addresses, into multiple columns.
+        """Transforms the one column from X, containing the email addresses,
+        into multiple columns.
 
         Args:
             X (pandas.DataFrame): DataFrame to transform.
@@ -182,8 +180,8 @@ def __num_of_words(string: str) -> int:
 
 
 class StringSimilarityTransformer(BaseTransformer):
-    """
-    Calculates the similarity between two strings using the `gestalt pattern matching` algorithm from the `SequenceMatcher` class.
+    """Calculates the similarity between two strings using the `gestalt pattern
+    matching` algorithm from the `SequenceMatcher` class.
 
     Example:
     ```python
@@ -215,8 +213,7 @@ def __init__(self, features: Tuple[str, str]) -> None:
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Calculates the similarity of two strings provided in `features`.
+        """Calculates the similarity of two strings provided in `features`.
 
         Args:
             X (pandas.DataFrame): DataFrame to transform.
@@ -253,8 +250,7 @@ def __normalize_string(string: str) -> str:
 
 
 class PhoneTransformer(BaseTransformer):
-    """
-    Transforms a phone number into multiple features.
+    """Transforms a phone number into multiple features.
 
     Example:
     ```python
@@ -293,8 +289,7 @@ def __init__(
         self.error_value = error_value
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Calculates the similarity of two strings provided in `features`.
+        """Calculates the similarity of two strings provided in `features`.
 
         Args:
             X (pandas.DataFrame): DataFrame to transform.
@@ -340,8 +335,8 @@ def __phone_to_float(
 
 
 class StringSlicerTransformer(BaseTransformer):
-    """
-    Slices all entries of specified string features using the `slice()` function.
+    """Slices all entries of specified string features using the `slice()`
+    function.
 
     Note: The arguments for the `slice()` function are passed as a tuple. This shares
     the python quirk of writing a tuple with a single argument with the trailing comma.
@@ -379,8 +374,7 @@ def __init__(
         self.features = features
 
     def transform(self, X: pd.DataFrame) -> pd.DataFrame:
-        """
-        Slices the strings of specified features in the dataframe.
+        """Slices the strings of specified features in the dataframe.
 
         Args:
             X (pandas.DataFrame): DataFrame to transform.
diff --git a/src/sk_transformers/utils.py b/src/sk_transformers/utils.py
index 6e5937c..248b0f0 100644
--- a/src/sk_transformers/utils.py
+++ b/src/sk_transformers/utils.py
@@ -82,8 +82,8 @@ def check_ready_to_transform(
 
 
 def check_data(X: pd.DataFrame, y: pd.Series, check_nans: bool = True) -> None:
-    """
-    Checks if the data has the correct types, shapes and does not contain any missing values.
+    """Checks if the data has the correct types, shapes and does not contain
+    any missing values.
 
     Args:
         X (pandas.DataFrame): The features.
@@ -111,9 +111,9 @@ def check_data(X: pd.DataFrame, y: pd.Series, check_nans: bool = True) -> None:
 def prepare_categorical_data(
     X: pd.DataFrame, categories: List[Tuple[str, int]]
 ) -> pd.DataFrame:
-    """
-    Checks for the validity of the categorical features inside the dataframe.
-    And prepares the data for further processing by changing the `dtypes`.
+    """Checks for the validity of the categorical features inside the
+    dataframe. And prepares the data for further processing by changing the
+    `dtypes`.
 
     Args:
         X (pandas.DataFrame): The dataframe containing the categorical features.
diff --git a/tests/test_transformer/test_generic_transformer.py b/tests/test_transformer/test_generic_transformer.py
index d892972..2ecfff0 100644
--- a/tests/test_transformer/test_generic_transformer.py
+++ b/tests/test_transformer/test_generic_transformer.py
@@ -127,7 +127,6 @@ def test_functions_transformer_raises_error(X) -> None:
 
 
 def test_map_transformer_in_pipeline(X) -> None:
-
     pipeline = make_pipeline(MapTransformer([("a", lambda x: x**2)]))
     result = pipeline.fit_transform(X)
     expected = np.array([1, 4, 9, 16, 25, 36, 49, 64, 81, 100])