One Hot Label Encoding Scikit_learn convert back to Data Frame
Should i convert it back to a data frame? why not?


  If you have some specific requirements like, saving data in
  a file or want to perform some specific operations which can be run
  better on DataFrame, then its a good choice to convert it back to
  dataframe. Otherwise it should be ok to go with numpy array, even
  Scikit_learn different algo takes numpy array as an input.


what is the best practice to merge X with my 1 numerical feature now ?


  I can share my experience and what exactly I did. 
  
  
  Save separately and drop the categorical feature and move rest of the features in to numpy array.
  Convert categorical features in to OneHot encoding.
  Concatenate OneHot Encoding numpy array with rest of the features and consume this array for model training.