[英]group by multiple columns and get a sum and count
我正在嘗試創建一個單一的數據框,可以在其中按年份、季節和聯賽可視化 5 個頻繁禁止字符。 我最初的 df 看起來像這樣:
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
我希望它最后看起來像這樣:
Year Season League Top 5 bans
2015 Spring EULCS [(Zed, 49), (Kassadin, 39), (Cassiopeia, 34), (RekSai, 33), (Nidalee, 30)]
在這一點上,我一直試圖讓它有意義,所以我嘗試了這個:
bans_info.groupby(['Year','Season', 'League', 'ban_1', 'ban_2', 'ban_3', 'ban_4', 'ban_5',]).sum()
和這個:
bans_info.groupby(['Year', 'Season', 'League']).ban_1.value_counts() 但最后還是沒有得到它我試圖單獨制作它但它變得太亂了
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')
您需要使用.agg
然后傳入列名和函數的字典。
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.