<p>好的,我设法得到了我的答案,我把它贴在这里给其他有同样问题的人。以下是我所做的:</p>
<pre><code>
# group by home and away and get the mean from HomeGoals and AwayGoals
final = dataset.groupby(['Home','Away'], as_index=False).agg({'HG': ['mean'], 'AG': ['mean']})
#count all the matches where one HomeTeam encountered the same AwayTeam, by a random column, it will get the same 'count' for every column
total_matches = dataset.groupby(['Home','Away'], as_index=False).AvgA.transform('count')
#set the column total_matches with total matches :)
dataset['total_matches'] = total_matches
def functie(home, away):
# get the results from big dataset where I have all the matches from 6-7 years
# and list all the 'Some Home Team' vs 'Some Away Team'
subset = dataset.loc[(dataset.Home==home)&(dataset.Away==away)]
#take the value of column 'total_matches' from first row, it's all the same on the nth
#row
x = subset['total_matches'].iloc[0]
if (x < 3):
print("Less than three matches" , x)
else:
if(x >= 3):
print("More than three matches" , x)
functie('Astra', 'CFR Cluj')
#gives the output 10
functie('Astra', 'Bistrita')
#gives the output 1
</code></pre>