v0.6.30

Author: bartzbeielstein

pyproject.toml

@@ -7,7 +7,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "spotPython"
-version = "0.6.29"
+version = "0.6.30"
 authors = [
   { name="T. Bartz-Beielstein", email="tbb@bartzundbartz.de" }
 ]

src/spotPython/plot/validation.py

@@ -128,7 +128,7 @@ def plot_roc_from_dataframes(
     alpha: float = 0.8,
     model_names: List[str] = None,
     target_column: str = None,
-    show=True,
+    show: bool = True,
 ) -> None:
     """
     Plot ROC curve for a list of dataframes from model evaluations.

src/spotPython/utils/eda.py

@@ -280,7 +280,7 @@ def plot_sns_heatmap(
     fmt=".5f",
     linewidths=0.5,
     annot_kws={"size": 8},
-):
+) -> None:
     """
     Plots a heatmap of the correlation matrix of the given DataFrame.
 
@@ -296,7 +296,7 @@ def plot_sns_heatmap(
         annot_kws (dict): Keyword arguments for annotations.
 
     Returns:
-        None
+        (NoneType): None
 
     Example:
         >>> import pandas as pd
@@ -320,15 +320,15 @@ def plot_sns_heatmap(
     plt.gcf().clear()
 
 
-def count_missing_data(df):
+def count_missing_data(df) -> pd.DataFrame:
     """
     Counts the number of missing values in each column of the given DataFrame.
 
     Args:
         df (pd.DataFrame): DataFrame containing the data to be counted.
 
     Returns:
-        pd.DataFrame: DataFrame containing the number of missing values in each column.
+        (pd.DataFrame): DataFrame containing the number of missing values in each column.
 
     Example:
         >>> import pandas as pd
@@ -346,7 +346,9 @@ def count_missing_data(df):
     return missing_df
 
 
-def plot_missing_data(df, relative=False, figsize=(7, 5), color="grey", xlabel="Missing Data", title="Missing Data"):
+def plot_missing_data(
+    df, relative=False, figsize=(7, 5), color="grey", xlabel="Missing Data", title="Missing Data"
+) -> None:
     """
     Plots a horizontal bar chart of the number of missing values in each column of the given DataFrame.
 
@@ -359,7 +361,7 @@ def plot_missing_data(df, relative=False, figsize=(7, 5), color="grey", xlabel="
         title (str): Title for the plot.
 
     Returns:
-        None
+        (NoneType): None
 
     Example:
         >>> import pandas as pd