text: Title: Add add_count and add_total functions
  Body: I know there is functionality with groupby_agg here, so I have been going back and forth on this one.  But like the tidyverse there are helper functions the are more direct like tally or add_count, where you could use summarize() and count() or n() together to get the same output.  
  
  I am not deeply invested in this suggestion, so if you think that groupby_agg can work here alone, I am fine with that.  
  
  Here are the two proposed functions I could possibly add:
  
  add_count function
  ```
  @pf.register_dataframe_method
  def add_count(df: pd.DataFrame(), count_column: str, new_column_name: str, include_na: bool):
      """Add countby column on target column"""  
      
      if include_na == True:
          df[new_column_name] = df.groupby([count_column])[count_column].transform('count')
          num = df[new_column_name].isna().sum()
          df[new_column_name].fillna(num, inplace= True)
          return df
      
      else:
          df[new_column_name] = df.groupby([count_column])[count_column].transform('count')
          return df
  
  ```
  
  add_total function
  ```
  @pf.register_dataframe_method
  def add_total(df: pd.DataFrame(), sum_columns: list, new_column_name: str, axis: int, skipna: bool):
      """Add countby column on target column"""  
      
      if axis == 1:
          df[new_column_name] = df[sum_columns].sum(axis= axis, skipna = skipna )
          return df
  
      else:
          df[new_column_name] = df[sum_columns].sum(axis= axis, skipna = skipna ).sum()
          return df
  ```