Optimise frame wide character replacement

A large fraction of time in the initial read was doing the removal of
any and all instances of the # character. If we use the fact that only
string and object column types will contain this character after
parsing with read_fwf we can run on fewer columns and don't need to use
regex, saving time.

Author: php1ic

src/nuclearmasses/io/ame_mass_parse.py

@@ -97,7 +97,8 @@ def read_file(self) -> pd.DataFrame:
         )
         # We use the NUBASE data to define whether or not an isotope is experimentally measured,
         # so for this data we'll just drop any and all '#' characters
-        df = df.replace("#", "", regex=True)
+        str_cols = df.select_dtypes(include=["object", "string"]).columns
+        df[str_cols] = df[str_cols].astype(str).apply(lambda s: s.str.replace("#", "", regex=False))
 
         if self.year == 1983:
             # The column headers and units are repeated in the 1983 table

src/nuclearmasses/io/ame_reaction_1_parse.py

@@ -95,7 +95,8 @@ def read_file(self) -> pd.DataFrame:
         )
         # We use the NUBASE data to define whether or not an isotope is experimentally measured,
         # so for this data we'll just drop any and all '#' characters
-        df = df.replace("#", "", regex=True)
+        str_cols = df.select_dtypes(include=["object", "string"]).columns
+        df[str_cols] = df[str_cols].astype(str).apply(lambda s: s.str.replace("#", "", regex=False))
 
         if self.year == 1983:
             # The column headers and units are repeated in the 1983 table

src/nuclearmasses/io/ame_reaction_2_parse.py

@@ -95,7 +95,8 @@ def read_file(self) -> pd.DataFrame:
         )
         # We use the NUBASE data to define whether or not an isotope is experimentally measured,
         # so for this data we'll just drop any and all '#' characters
-        df = df.replace("#", "", regex=True)
+        str_cols = df.select_dtypes(include=["object", "string"]).columns
+        df[str_cols] = df[str_cols].astype(str).apply(lambda s: s.str.replace("#", "", regex=False))
 
         if self.year == 1983:
             # The column headers and units are repeated in the 1983 table

src/nuclearmasses/io/nubase_parse.py

@@ -185,7 +185,8 @@ def read_file(self) -> pd.DataFrame:
         # We use the NUBASE data to define whether or not an isotope is experimentally measured,
         df["Experimental"] = ~df["NUBASEMassExcess"].astype("string").str.contains("#", na=False)
         # Once we have used the '#' to determine if it's experimental or not, we can remove all instances of it
-        df = df.replace("#", "", regex=True)
+        str_cols = df.select_dtypes(include=["object", "string"]).columns
+        df[str_cols] = df[str_cols].astype(str).apply(lambda s: s.str.replace("#", "", regex=False))
 
         df = self.parse_half_life(df)
         df = self.calculate_relative_error(df)