pyhon用.groupby()作分组运算实例代码

这篇文章主要讲解了"pyhon用.groupby()作分组运算实例代码"，文中的讲解内容简单清晰，易于学习与理解，下面请大家跟着小编的思路慢慢深入，一起来研究和学习"pyhon用.groupby()作分组运算实例代码"吧！

1. 构造数据源，小试一下牛刀

import pandas as pd df = pd.DataFrame({"品类":["蔬菜","蔬菜","水果","水果","蔬菜","蔬菜","水果","水产","水产","水产"],                   "数量":[10,20,30,40,50,60,70,80,90,100]})df

2. 实操，确认方法是否可行

df.sort_values(["品类", "数量"],ascending=[1,0],inplace=True) df_grouped = df.groupby(["品类"]).head(2)df_grouped

显然可行

2. 1 | 0，True or False，"真" 或 "假"

import pandas as pd df1 = pd.DataFrame({"品类":["蔬菜","蔬菜","水果","水果","蔬菜","蔬菜","水果","水产","水产","水产"],                    "数量":[10,20,30,40,50,60,70,80,90,100]})df1

df.sort_values(["品类", "数量"],ascending=[True, False],inplace=True) df1_grouped = df.groupby(["品类"]).head(3)df1_grouped

3. 再多加一点层次索引

import pandas as pd df2 = pd.read_excel(r"D:\我的文档\jupyter.xlsx",sheet_name = 1)df2

df2.sort_values(["品类", "销售数量"],ascending=[True, False],inplace=True) df2_grouped = df2.groupby(["品类"]).head(3)df2_grouped

df2.sort_values(["城市","品类", "销售数量"],ascending=[True,True, False],inplace=True) df2_grouped = df2.groupby(["品类"]).head(3)df2_grouped

df2.sort_values(["城市","品类", "销售数量"],ascending=[True,False, False],inplace=True) df2_grouped = df2.groupby(["品类","城市"]).head(3)df2_grouped

感谢各位的阅读，以上就是"pyhon用.groupby()作分组运算实例代码"的内容了，经过本文的学习后，相信大家对pyhon用.groupby()作分组运算实例代码这一问题有了更深刻的体会，具体使用情况还需要大家实践验证。这里是，小编将为大家推送更多相关知识点的文章，欢迎关注！