I have the following dictionary dict_group containing several pandas series as value whose keys are a string of group name:
{'Group A': Pos Team Pld W D L GF GA GD Pts
0 1 Netherlands 3 2 1 0 5 1 +4 7
1 2 Senegal 3 2 0 1 5 4 +1 6
2 3 Ecuador 3 1 1 1 4 3 +1 4
3 4 Qatar (H) 3 0 0 3 1 7 −6 0,
'Group B': Pos Team Pld W D L GF GA GD Pts
0 1 England 3 2 1 0 9 2 +7 7
1 2 United States 3 1 2 0 2 1 +1 5
2 3 Iran 3 1 0 2 4 7 −3 3
3 4 Wales 3 0 1 2 1 6 −5 1,
'Group C': Pos Team Pld W D L GF GA GD Pts
0 1 Argentina 3 2 0 1 5 2 +3 6
1 2 Poland 3 1 1 1 2 2 0 4
2 3 Mexico 3 1 1 1 2 3 −1 4
3 4 Saudi Arabia 3 1 0 2 3 5 −2 3,
'Group D': Pos Team Pld W D L GF GA GD Pts
0 1 France 3 2 0 1 6 3 +3 6
1 2 Australia 3 2 0 1 3 4 −1 6
2 3 Tunisia 3 1 1 1 1 1 0 4
3 4 Denmark 3 0 1 2 1 3 −2 1,
each series contains a ‘Pos’ column and a ‘Team’ column, I am trying to access the Pos corresponding to a selected team, example if I chose Senegal in group A I want to retrieve the value 2, can you please help me figure this out
>Solution :
If select in dictionary of DataFrames by key get DataFrame, then convert Team to index, so possible use DataFrame.loc:
df = d['Group A']
out = df.set_index('Team').loc['Senegal', 'Pos']
Or use DataFrame.loc with boolean indexing – but then necessary convert one element Series to scalar:
out = df.loc[df['Team'].eq('Senegal'), 'Pos'].iat[0]
out = next(iter(df.loc[df['Team'].eq('Senegal'), 'Pos']), 'no match')