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這篇文章主要講解了“pyhon用.groupby()作分組運算實例代碼”,文中的講解內(nèi)容簡單清晰,易于學(xué)習(xí)與理解,下面請大家跟著小編的思路慢慢深入,一起來研究和學(xué)習(xí)“pyhon用.groupby()作分組運算實例代碼”吧!
1. 構(gòu)造數(shù)據(jù)源,小試一下牛刀
import pandas as pd df = pd.DataFrame({"品類":["蔬菜","蔬菜","水果","水果","蔬菜","蔬菜","水果","水產(chǎn)","水產(chǎn)","水產(chǎn)"], "數(shù)量":[10,20,30,40,50,60,70,80,90,100]}) df
2. 實操,確認方法是否可行
df.sort_values(["品類", "數(shù)量"],ascending=[1,0],inplace=True) df_grouped = df.groupby(["品類"]).head(2) df_grouped
顯然可行
2. 1 | 0,True or False,“真” 或 “假”
import pandas as pd df1 = pd.DataFrame({"品類":["蔬菜","蔬菜","水果","水果","蔬菜","蔬菜","水果","水產(chǎn)","水產(chǎn)","水產(chǎn)"], "數(shù)量":[10,20,30,40,50,60,70,80,90,100]}) df1
df.sort_values(["品類", "數(shù)量"],ascending=[True, False],inplace=True) df1_grouped = df.groupby(["品類"]).head(3) df1_grouped
3. 再多加一點層次索引
import pandas as pd df2 = pd.read_excel(r"D:\我的文檔\jupyter.xlsx",sheet_name = 1) df2
df2.sort_values(["品類", "銷售數(shù)量"],ascending=[True, False],inplace=True) df2_grouped = df2.groupby(["品類"]).head(3) df2_grouped
df2.sort_values(["城市","品類", "銷售數(shù)量"],ascending=[True,True, False],inplace=True) df2_grouped = df2.groupby(["品類"]).head(3) df2_grouped
df2.sort_values(["城市","品類", "銷售數(shù)量"],ascending=[True,False, False],inplace=True) df2_grouped = df2.groupby(["品類","城市"]).head(3) df2_grouped
感謝各位的閱讀,以上就是“pyhon用.groupby()作分組運算實例代碼”的內(nèi)容了,經(jīng)過本文的學(xué)習(xí)后,相信大家對pyhon用.groupby()作分組運算實例代碼這一問題有了更深刻的體會,具體使用情況還需要大家實踐驗證。這里是億速云,小編將為大家推送更多相關(guān)知識點的文章,歡迎關(guān)注!
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