Printing All Rows In Each Level Of MultiIndex Pd.DataFrame In One Row

I have a dataframe which was converted into a multiIndex dataframe after doing groupby() and aggregation. In[1]: mydata = [['Team1', 'Player1', 'idTrip13', 133], ['Team2', 'Player

Solution 1:

1. Iterate through the 0th level (team) using groupby().

   for team, df2 in player_total.groupby(level = 0):
   

   For example at the second iteration, it will return a dataframe for Team2:

                   trips   time
   team  player              
   Team2 Player293     1  17656
         Player333     1  18373
   

2. Use reset_index() to drop the team index column and make the player index column as part of the dataframe.

   >>>team_df = df2.reset_index(level = 0, drop = True).reset_index()
   >>>team_df
         player  trips   time
   0  Player293     1  17656
   1  Player333     1  18373
   

3. Convert that dataframe into a list of lists so we can iterate through each player.

   team_df.values.tolist()
   >>>[['Player293', 1, 17656], ['Player333', 1, 18373]]
   

4. When printing we have to map the integers to a string, and use the end parameter of the print function to print a semicolon instead of printing a new line at the end.

   >>>for player in team_df.values.tolist():
          print(': '.join(map(str, player)), end = '; ')
   >>>Player293: 1: 17656; Player333: 1: 18373; 
   

The full solution:

from __future__ import print_function

#iterate through each team
for team, df2 in player_total.groupby(level = 0):
    print(team, end = '\t')
    #drop the 0th level (team) and move the first level (player) as the index
    team_df = df2.reset_index(level = 0, drop = True).reset_index()
    #iterate through each player on the team and print player, trip, and time
    for player in team_df.values.tolist():
        print(': '.join(map(str, player)), end = '; ')
    #After printing all players insert a new line
    print()

Output:

Player1: 2: 19526; 
Player293: 1: 17656; Player333: 1: 18373; 
Player20: 1: 1883; Player22: 1: 17338899;