我正在尝试创建一个数据框,可以按年份,季节和联赛显示5个常见禁令字符。 我最初的df看起来像这样:
League Year Season ban_1 ban_2 ban_3 ban_4 ban_5
0 NALCS 2015 Spring Rumble Kassadin Lissandra NaN NaN
1 NALCS 2015 Spring Tristana Leblanc Nidalee NaN NaN
2 NALCS 2015 Spring Kassadin Sivir Lissandra NaN NaN
3 NALCS 2015 Spring RekSai Janna Leblanc NaN NaN
4 NALCS 2015 Spring JarvanIV Lissandra Kassadin NaN NaN
最后,我希望它看起来像这样:
Year Season League Top 5 bans
2015 Spring EULCS [(Zed, 49), (Kassadin, 39), (Cassiopeia, 34), (RekSai, 33), (Nidalee, 30)]
在这一点上,我一直在试图使之有意义,所以我尝试了这一点:
bans_info.groupby(['Year','Season', 'League', 'ban_1', 'ban_2', 'ban_3', 'ban_4', 'ban_5',]).sum()
这:
bans_info.groupby(['Year','Season','League'])。ban_1.value_counts() 但最后还是没有得到它,我尝试将其分开制作,但变得太乱了
b1 = bans_info.groupby(['Year', 'Season', 'League']).ban_1.value_counts()
b2 = bans_info.groupby(['Year', 'Season', 'League']).ban_2.value_counts()
b12 = pd.merge(b1, b2, how='outer', on ='Year')