Possibility to remove all NaNs features or not after featurization.

Author: gbrunin

modnet/featurizers/utils.py

@@ -3,20 +3,22 @@
 __all__ = ("clean_df",)
 
 
-def clean_df(df):
+def clean_df(df, drop_allnan: bool = True):
     """Cleans dataframe by dropping missing values, replacing NaN's and infinities
     and selecting only columns containing numerical data.
 
     Args:
         df (pd.DataFrame): the dataframe to clean.
+        drop_allnan: if True, clean_df will remove features that are fully NaNs.
 
     Returns:
         pandas.DataFrame: the cleaned dataframe.
 
     """
 
     df = df.select_dtypes(include="number")
-    df = df.dropna(axis=1, how="all")
+    if drop_allnan:
+        df = df.dropna(axis=1, how="all")
     df = df.replace([np.inf, -np.inf, np.nan], np.nan)
 
     return df