17-numpy笔记-莫烦pandas-5
代码
import pandas as pd
import numpy as np left=pd.DataFrame({'key':['K0','K1','K2','K3'],
'A':['A0','A1','A3','A3'],
'B':['B0','B1','B2','B3'],}) right=pd.DataFrame({'key':['K0','K1','K2','K3'],
'C':['C0','C1','C3','C3'],
'D':['D0','D1','D2','D3'],}) print('-1-')
print(left)
print(right) res = pd.merge(left,right,on='key')
print(res) left=pd.DataFrame({'key1':['K0','K0','K1','K2'],
'key2':['K0','K1','K0','K1'],
'A':['A0','A1','A3','A3'],
'B':['B0','B1','B2','B3'],}) right=pd.DataFrame({'key1':['K0','K1','K1','K2'],
'key2':['K0','K0','K0','K0'],
'C':['C0','C1','C3','C3'],
'D':['D0','D1','D2','D3'],}) print('-2-')
res = pd.merge(left,right,on=['key1','key2'])
print(left)
print(right)
print(res) # default
print('-3-')
res = pd.merge(left,right,on=['key1','key2'],how='inner')
print(left)
print(right)
print(res) print('-4-')
res = pd.merge(left,right,on=['key1','key2'],how='outer')
print(left)
print(right)
print(res) print('-5-')
res = pd.merge(left,right,on=['key1','key2'],how='right')
print(left)
print(right)
print(res) print('-6-')
res = pd.merge(left,right,on=['key1','key2'],how='left')
print(left)
print(right)
print(res) print('-7-')
df1 = pd.DataFrame({'col1':[0,1],'col_left':['a','b']})
df2 = pd.DataFrame({'col1':[1,2,2],'col_right':[2,2,2]})
print(df1)
print(df2)
res = pd.merge(df1,df2,on='col1',how='outer',indicator=True)
print(res) res = pd.merge(df1,df2,on='col1',how='outer',indicator=True)
print(res) res = pd.merge(df1,df2,on='col1',how='outer',indicator='indicator_column')
print(res) df1 = pd.DataFrame({'A':['A0','A1','A2'],
'B':['B0','B1','B2']},
index=['K0','K1','K2']) df2 = pd.DataFrame({'C':['C0','C1','C2'],
'D':['D0','D1','D2']},
index=['K0','K1','K2']) print(df1)
print(df2) print('-8-')
res=pd.merge(left,right,left_index=True,right_index=True,how='outer')
print(res) print('-9-')
res=pd.merge(left,right,left_index=True,right_index=True,how='inner')
print(res) boys = pd.DataFrame({'k':['K0','K1','K2'],'age':[1,2,3]})
girls = pd.DataFrame({'k':['K0','K0','K3'],'age':[4,5,6]}) print('-10-')
print(boys)
print(girls) res = pd.merge(boys, girls, on='k', suffixes=['_boy','_girl'],how='inner')
print(res) res = pd.merge(boys, girls, on='k', suffixes=['_boy','_girl'],how='outer')
print(res)
输出
-1-
key A B
0 K0 A0 B0
1 K1 A1 B1
2 K2 A3 B2
3 K3 A3 B3
key C D
0 K0 C0 D0
1 K1 C1 D1
2 K2 C3 D2
3 K3 C3 D3
key A B C D
0 K0 A0 B0 C0 D0
1 K1 A1 B1 C1 D1
2 K2 A3 B2 C3 D2
3 K3 A3 B3 C3 D3
-2-
key1 key2 A B
0 K0 K0 A0 B0
1 K0 K1 A1 B1
2 K1 K0 A3 B2
3 K2 K1 A3 B3
key1 key2 C D
0 K0 K0 C0 D0
1 K1 K0 C1 D1
2 K1 K0 C3 D2
3 K2 K0 C3 D3
key1 key2 A B C D
0 K0 K0 A0 B0 C0 D0
1 K1 K0 A3 B2 C1 D1
2 K1 K0 A3 B2 C3 D2
-3-
key1 key2 A B
0 K0 K0 A0 B0
1 K0 K1 A1 B1
2 K1 K0 A3 B2
3 K2 K1 A3 B3
key1 key2 C D
0 K0 K0 C0 D0
1 K1 K0 C1 D1
2 K1 K0 C3 D2
3 K2 K0 C3 D3
key1 key2 A B C D
0 K0 K0 A0 B0 C0 D0
1 K1 K0 A3 B2 C1 D1
2 K1 K0 A3 B2 C3 D2
-4-
key1 key2 A B
0 K0 K0 A0 B0
1 K0 K1 A1 B1
2 K1 K0 A3 B2
3 K2 K1 A3 B3
key1 key2 C D
0 K0 K0 C0 D0
1 K1 K0 C1 D1
2 K1 K0 C3 D2
3 K2 K0 C3 D3
key1 key2 A B C D
0 K0 K0 A0 B0 C0 D0
1 K0 K1 A1 B1 NaN NaN
2 K1 K0 A3 B2 C1 D1
3 K1 K0 A3 B2 C3 D2
4 K2 K1 A3 B3 NaN NaN
5 K2 K0 NaN NaN C3 D3
-5-
key1 key2 A B
0 K0 K0 A0 B0
1 K0 K1 A1 B1
2 K1 K0 A3 B2
3 K2 K1 A3 B3
key1 key2 C D
0 K0 K0 C0 D0
1 K1 K0 C1 D1
2 K1 K0 C3 D2
3 K2 K0 C3 D3
key1 key2 A B C D
0 K0 K0 A0 B0 C0 D0
1 K1 K0 A3 B2 C1 D1
2 K1 K0 A3 B2 C3 D2
3 K2 K0 NaN NaN C3 D3
-6-
key1 key2 A B
0 K0 K0 A0 B0
1 K0 K1 A1 B1
2 K1 K0 A3 B2
3 K2 K1 A3 B3
key1 key2 C D
0 K0 K0 C0 D0
1 K1 K0 C1 D1
2 K1 K0 C3 D2
3 K2 K0 C3 D3
key1 key2 A B C D
0 K0 K0 A0 B0 C0 D0
1 K0 K1 A1 B1 NaN NaN
2 K1 K0 A3 B2 C1 D1
3 K1 K0 A3 B2 C3 D2
4 K2 K1 A3 B3 NaN NaN
-7-
col1 col_left
0 0 a
1 1 b
col1 col_right
0 1 2
1 2 2
2 2 2
col1 col_left col_right _merge
0 0 a NaN left_only
1 1 b 2.0 both
2 2 NaN 2.0 right_only
3 2 NaN 2.0 right_only
col1 col_left col_right _merge
0 0 a NaN left_only
1 1 b 2.0 both
2 2 NaN 2.0 right_only
3 2 NaN 2.0 right_only
col1 col_left col_right indicator_column
0 0 a NaN left_only
1 1 b 2.0 both
2 2 NaN 2.0 right_only
3 2 NaN 2.0 right_only
A B
K0 A0 B0
K1 A1 B1
K2 A2 B2
C D
K0 C0 D0
K1 C1 D1
K2 C2 D2
-8-
key1_x key2_x A B key1_y key2_y C D
0 K0 K0 A0 B0 K0 K0 C0 D0
1 K0 K1 A1 B1 K1 K0 C1 D1
2 K1 K0 A3 B2 K1 K0 C3 D2
3 K2 K1 A3 B3 K2 K0 C3 D3
-9-
key1_x key2_x A B key1_y key2_y C D
0 K0 K0 A0 B0 K0 K0 C0 D0
1 K0 K1 A1 B1 K1 K0 C1 D1
2 K1 K0 A3 B2 K1 K0 C3 D2
3 K2 K1 A3 B3 K2 K0 C3 D3
-10-
k age
0 K0 1
1 K1 2
2 K2 3
k age
0 K0 4
1 K0 5
2 K3 6
k age_boy age_girl
0 K0 1 4
1 K0 1 5
k age_boy age_girl
0 K0 1.0 4.0
1 K0 1.0 5.0
2 K1 2.0 NaN
3 K2 3.0 NaN
4 K3 NaN 6.0
17-numpy笔记-莫烦pandas-5的更多相关文章
- 16-numpy笔记-莫烦pandas-4
代码 import pandas as pd import numpy as np dates = pd.date_range('20130101', periods=6) df=pd.DataFra ...
- 15-numpy笔记-莫烦pandas-3
代码 import pandas as pd import numpy as np dates = pd.date_range('20130101', periods=6) df=pd.DataFra ...
- 14-numpy笔记-莫烦pandas-2
代码 import pandas as pd import numpy as np dates = pd.date_range('20130101', periods=6) df=pd.DataFra ...
- 18-numpy笔记-莫烦pandas-6-plot显示
代码 import pandas as pd import numpy as np import matplotlib.pyplot as plt data = pd.Series(np.random ...
- 13-numpy笔记-莫烦pandas-1
代码 import pandas as pd import numpy as np s = pd.Series([1,3,6,np.nan, 44,1]) print('-1-') print(s) ...
- 11-numpy笔记-莫烦基础操作1
代码 import numpy as np array = np.array([[1,2,5],[3,4,6]]) print('-1-') print('数组维度', array.ndim) pri ...
- 12-numpy笔记-莫烦基本操作2
代码 import numpy as np A = np.arange(3,15) print('-1-') print(A) print('-2-') print(A[3]) A = np.aran ...
- Python pandas & numpy 笔记
记性不好,多记录些常用的东西,真·持续更新中::先列出一些常用的网址: 参考了的 莫烦python pandas DOC numpy DOC matplotlib 常用 习惯上我们如此导入: impo ...
- tensorflow学习笔记-bili莫烦
bilibili莫烦tensorflow视频教程学习笔记 1.初次使用Tensorflow实现一元线性回归 # 屏蔽警告 import os os.environ[' import numpy as ...
随机推荐
- shellnet运行train_val_seg.py
1.semantic3d数据集准备:prepare_semantic3d_data.py 11个测试数据集(.txt文件): 假如运行的是室外点云数据集“seg_semantic3d”,可能需要做以下 ...
- WEB 中的文件下载(待修改、完善)
在 WEB 开发中,我们会期望用户在点击某个链接的时候,下载一个文件(不管这个文件能不能被浏览器解析,都要下载).以前接触过一种方式,就是在响应 header 中设置 force-download : ...
- react细节
1.在函数式组件中使用 类型和默认值 function App({ name }) { return ( <div> <h1>{name}</h1> </di ...
- 使用mybatis动态where字句方法
上篇文章介绍了如何使用mybatis-generator生成实体类.Mapper接口代码,其中生成的Mapper接口代码是不带ByExample方法的.本篇文章将介绍如何使用mybatis-gener ...
- STS 重写父类方法的操作
本来这种东西真的没什么好写的,但是很多时候真的是要用到的,不知道的话自己手动敲,会累死人的.所以记录在这里,自己的笔记,有需要的赶紧拿去,省的手动录入那么辛苦. 在代码窗口点击右键,依次选择“Sour ...
- JeeSite | 访问控制权限
在各种后台系统中都会涉及到权限的管控,从功能权限的管控,到数据权限的管控,都是为了让系统的在使用的过程中更加的安全.功能权限管控是对针对不同的角色可以进行不同的功能操作,而数据权限管控是针对不同的角色 ...
- 缘起 Dubbo ，讲讲 Spring XML Schema 扩展机制
背景 在 Dubbo 中,可以使用 XML 配置相关信息,也可以用来引入服务或者导出服务.配置完成,启动工程,Spring 会读取配置文件,生成注入 相关 Bean.那 Dubbo 如何实现自定义 X ...
- 【01】Nginx：编译安装/动态添加模块
写在前面的话 说起 Nginx,别说运维,就是很多开发人员也很熟悉,毕竟如今已经 2019 年了,Apache 更多的要么成为了历史,要么成为了历史残留. 我们在提及 Nginx 的时候,一直在强调他 ...
- 【随笔】CLR:.net的类型，内部到底长啥样？
前言 一提到.net的类型,首当其冲的就是“引用类型”.“值类型”:我们在面试中,也会经常被问“来说说值类型和引用类型....”,这时候第一反应就是:“哎呀,这还不简单,值类型是传递的值的copy,值 ...
- 重温CLR（十七）程序集加载和反射
本章主要讨论在编译时对一个类型一无所知的情况下,如何在运行时发现类型的信息.创建类型的实例以及访问类型的成员.可利用本章讲述的内容创建动态可扩展应用程序. 反射使用的典型场景一般是由一家公司创建宿主应 ...