original_docstring: 
      loads all the log files in JSON format, process them, and load them into appropriate columns and tables (e.g. time, users, and sonplays tables)
      
docstring: loads all the log files in JSON format, process them, and load them into appropriate columns and tables
docstring_tokens: loads all the log files in JSON format process them and load them into appropriate columns and tables
code: def process_log_file(cur, filepath):
      """
      loads all the log files in JSON format, process them, and load them into appropriate columns and tables (e.g. time, users, and sonplays tables)
      """
      # open log file
      df = pd.read_json(filepath, lines=True) #filepath format must be: r'..\file.jason'
      # filter by NextSong action
      df = df[df["page"] == "NextSong"]
      # convert timestamp column to datetime
      t = pd.to_datetime(df["ts"], unit='ms')
      # insert time data records
      time_data = list(zip(df["ts"], t.dt.hour, t.dt.day, t.dt.isocalendar().week, t.dt.month, t.dt.year, t.dt.weekday))
      column_labels = ['start_time', 'hour', 'day', 'week', 'month', 'year', 'weekday']
      time_df = pd.DataFrame(time_data, columns = column_labels)
  
      for i, row in time_df.iterrows():
          cur.execute(time_table_insert, list(row))
  
      # load user table
      user_column_labels = ['user_id', 'first_name', 'last_name', 'gender', 'level']
      user_data = list(zip(df["userId"], df["firstName"], df["lastName"], df["gender"],  df["level"]))
      user_df = pd.DataFrame(user_data, columns = user_column_labels)
      # insert user records
      for i, row in user_df.iterrows():
          cur.execute(user_table_insert, row)
      # insert songplay records
      for index, row in df.iterrows():
          # get songid and artistid from song and artist tables
          cur.execute(song_select, (row.song, row.artist, row.length))
          results = cur.fetchone()
          print(results)
          if results:
              songid, artistid = results
          else:
              songid, artistid = None, None
          print(results)
          print(songid, artistid)
          # insert songplay record
          songplay_data = row.sessionId, row.location, row.userAgent, pd.to_datetime(row.ts, unit='ms') , row.userId, artistid, songid, row.level
          cur.execute(songplay_table_insert, songplay_data)
code_tokens: def process_log_file ( cur , filepath ) : df = pd . read_json ( filepath , lines = True ) df = df [ df [ "page" ] == "NextSong" ] t = pd . to_datetime ( df [ "ts" ] , unit = 'ms' ) time_data = list ( zip ( df [ "ts" ] , t . dt . hour , t . dt . day , t . dt . isocalendar ( ) . week , t . dt . month , t . dt . year , t . dt . weekday ) ) column_labels = [ 'start_time' , 'hour' , 'day' , 'week' , 'month' , 'year' , 'weekday' ] time_df = pd . DataFrame ( time_data , columns = column_labels ) for i , row in time_df . iterrows ( ) : cur . execute ( time_table_insert , list ( row ) ) user_column_labels = [ 'user_id' , 'first_name' , 'last_name' , 'gender' , 'level' ] user_data = list ( zip ( df [ "userId" ] , df [ "firstName" ] , df [ "lastName" ] , df [ "gender" ] , df [ "level" ] ) ) user_df = pd . DataFrame ( user_data , columns = user_column_labels ) for i , row in user_df . iterrows ( ) : cur . execute ( user_table_insert , row ) for index , row in df . iterrows ( ) : cur . execute ( song_select , ( row . song , row . artist , row . length ) ) results = cur . fetchone ( ) print ( results ) if results : songid , artistid = results else : songid , artistid = None , None print ( results ) print ( songid , artistid ) songplay_data = row . sessionId , row . location , row . userAgent , pd . to_datetime ( row . ts , unit = 'ms' ) , row . userId , artistid , songid , row . level cur . execute ( songplay_table_insert , songplay_data )
short_docstring: loads all the log files in JSON format, process them, and load them into appropriate columns and tables (e.g.
short_docstring_tokens: loads all the log files in JSON format process them and load them into appropriate columns and tables ( e . g .
comment: """
      loads all the log files in JSON format, process them, and load them into appropriate columns and tables (e.g. time, users, and sonplays tables)
      """$SEP$# open log file$SEP$#filepath format must be: r'..\file.jason'$SEP$# filter by NextSong action$SEP$# convert timestamp column to datetime$SEP$# insert time data records$SEP$# load user table$SEP$# insert user records$SEP$# insert songplay records$SEP$# get songid and artistid from song and artist tables$SEP$# insert songplay record