本文介绍: ​Python利用pandas两个dataframe数据进行左联接/左关联(以左边为主体)、右联接/右关联(以右边为主体)、内联接(取交集)、外联接(取并集)操作案例实现代码目录joinleft joinright join之间区别左联接/左关联(以左边为主体)、右联接/右关联(以右边为主体)、内联接(取交集)、外联接(取并集)操作案例joinleft joinright join之间区别Database之SQLSever:SQL命令实现查询多表查询嵌套查询分页复杂

Python利用pandas两个dataframe数据进行左联接/左关联(以左边为主体)、右联接/右关联(以右边为主体)、内联接(取交集)、外联接(取并集)操作案例实现代码

目录

join、left join和right join之间区别

Database之SQLSever:SQL命令实现查询之多表查询、嵌套查询、分页复杂查询,删除表内重复记录数据、连接(join、left join和right join简介及其区别)等案例之详细攻略

左联接/左关联(以左边为主体)、右联接/右关联(以右边为主体)、内联接(取交集)、外联接(取并集)操作案例

实现代码


joinleft joinright join之间区别

Database之SQLSever:SQL命令实现查询多表查询嵌套查询分页复杂查询删除表内重复记录数据连接(joinleft join和right join简介及其区别)等案例之详细攻略

https://yunyaniu.blog.csdn.net/article/details/107620041

 

左联接/左关联(以左边为主体)、右联接/右关联(以右边为主体)、内联接(取交集)、外联接(取并集)操作案例

实现代码

# Python利用pandas两个dataframe数据进行左联接/左关联(以左边为主体)、右联接/右关联(以右边为主体)、内联接(取交集)、外联接(取并集)操作案例实现代码

import pandas as pd
import numpy as np
 
 
students_info={"student_num": ['1001',        '1002',           '1003',            '1004'],
               "name":        ['Bob',         'LiSa',           'Mary',            'Alan'],
               "major":       ['mechanical',  'philosophy',     'mathematics',  'computer'],
               "grade":       ['freshman',     'sophomore',     'junior',         'senior'],
               "sex":  ['男',          '女',                        '女',                        None,],   # 输出 None
               "age":  [np.nan,        28,                           38 ,                        '' ],   # 输出 
               "born": [pd.NaT,     pd.Timestamp("1990-01-01"),  pd.Timestamp("1980-01-01"),      ''],   # 输出 NaT
               }   

students_score={"name":        ['Bob',         'LiSa',           'Mary',            'Tom'],
               "chinese":      [85,              80,                 95,                98],
               "math":         [90,              95,                 85,                90],
               }
s_info_df = pd.DataFrame(students_info)
s_score_df = pd.DataFrame(students_score)

s_df_left = s_info_df.merge(s_score_df, left_on='name',right_on='name',how='left')
print('------------left:以左边为主体--------------')
print(s_df_left)

s_df_right = s_info_df.merge(s_score_df, left_on='name',right_on='name',how='right')
print('------------right:以右边为主体--------------')
print(s_df_right)

s_df_inner = s_info_df.merge(s_score_df, left_on='name',right_on='name',how='inner')
print('------------inner:取交集--------------')
print(s_df_inner)

s_df_outer = s_info_df.merge(s_score_df, left_on='name',right_on='name',how='outer')
print('------------outer:取并集--------------')
print(s_df_outer)

------------left:以左边为主体--------------
  student_num  name        major      grade  ...  age       born chinese  math
0        1001   Bob   mechanical   freshman  ...  NaN        NaT    85.0  90.0
1        1002  LiSa   philosophy  sophomore  ...   28 1990-01-01    80.0  95.0
2        1003  Mary  mathematics     junior  ...   38 1980-01-01    95.0  85.0
3        1004  Alan     computer     senior  ...             NaT     NaN   NaN

[4 rows x 9 columns]
------------right:以右边为主体--------------
  student_num  name        major      grade  sex  age       born  chinese  math
0        1001   Bob   mechanical   freshman    男  NaN        NaT       85    90
1        1002  LiSa   philosophy  sophomore    女   28 1990-01-01       80    95
2        1003  Mary  mathematics     junior    女   38 1980-01-01       95    85
3         NaN   Tom          NaN        NaN  NaN  NaN        NaT       98    90
------------inner:取交集--------------
  student_num  name        major      grade sex  age       born  chinese  math
0        1001   Bob   mechanical   freshman   男  NaN        NaT       85    90
1        1002  LiSa   philosophy  sophomore   女   28 1990-01-01       80    95
2        1003  Mary  mathematics     junior   女   38 1980-01-01       95    85
------------outer:取并集--------------
  student_num  name        major      grade  ...  age       born chinese  math
0        1001   Bob   mechanical   freshman  ...  NaN        NaT    85.0  90.0
1        1002  LiSa   philosophy  sophomore  ...   28 1990-01-01    80.0  95.0
2        1003  Mary  mathematics     junior  ...   38 1980-01-01    95.0  85.0
3        1004  Alan     computer     senior  ...             NaT     NaN   NaN
4         NaN   Tom          NaN        NaN  ...  NaN        NaT    98.0  90.0

[5 rows x 9 columns]

原文地址:https://blog.csdn.net/qq_41185868/article/details/129402505

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