我有一個索引和打印的列表；此處顯示的示例：[Home Team season 1. FC Kaiserslautern 2010/2011 48 2011/2012 24 1. FC K?ln 2008/2009 35 2009/2010 33 2010/2011 47 2011/2012 39 2014/2015 34 2015/2016 38 1. FC Nürnberg 2009/2010 32 2010/2011 47 2011/2012 38 2012/2013 39 2013/2014 37不過，我無法將其轉換為相同格式的 Pandas 數據幀。使用df = pd.DataFrame(df)創建一個單行數據框，所有內容都成束。我獲取列表的代碼是：df = []home_goals = leaguesFinal.groupby(('Home Team', 'season'))['home_team_goal'].sum()away_goals = leaguesFinal.groupby(('Away Team', 'season'))['away_team_goal'].sum()df.append((home_goals + away_goals))我只是想總結每支球隊每個賽季的主客場進球數。如果有更好的方法來做到這一點，一般我都會聽。雖然為了更容易操作，我最終還是想要一個數據框。
1 回答
茅侃侃
TA貢獻1842條經驗 獲得超22個贊
我相信需要rename_axis使用add和DataFrame使用相同名稱的 MultiIndex reset_index：
leaguesFinal = pd.DataFrame({
'Home Team': ['b','a','a','c','b','a'],
'Away Team': ['a','b','c','a','a','b'],
'season': ['2010/2011'] * 3 + ['2012/2013'] * 3,
'home_team_goal': [1,2,3,4,3,2],
'away_team_goal': [4,6,7,8,2,1]
})
print (leaguesFinal)
Home Team Away Team season home_team_goal away_team_goal
0 b a 2010/2011 1 4
1 a b 2010/2011 2 6
2 a c 2010/2011 3 7
3 c a 2012/2013 4 8
4 b a 2012/2013 3 2
5 a b 2012/2013 2 1
home_goals = leaguesFinal.groupby(['Home Team', 'season'])['home_team_goal'].sum()
away_goals = leaguesFinal.groupby(['Away Team', 'season'])['away_team_goal'].sum()
print (home_goals)
Home Team season
a 2010/2011 5
2012/2013 2
b 2010/2011 1
2012/2013 3
c 2012/2013 4
Name: home_team_goal, dtype: int64
print (away_goals)
Away Team season
a 2010/2011 4
2012/2013 10
b 2010/2011 6
2012/2013 1
c 2010/2011 7
Name: away_team_goal, dtype: int64
a = home_goals.rename_axis(['Team','season'])
b = away_goals.rename_axis(['Team','season'])
df = (a.add(b, fill_value=0)).reset_index(name='both')
print (df)
Team season both
0 a 2010/2011 9.0
1 a 2012/2013 12.0
2 b 2010/2011 7.0
3 b 2012/2013 4.0
4 c 2010/2011 7.0
5 c 2012/2013 4.0
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