Join on Multiple Columns

How to join two tables by multiple columns in SQL?

Yes: You can use Inner Join to join on multiple columns.

SELECT E.CaseNum, E.FileNum, E.ActivityNum, E.Grade, V.Score from Evaluation E
INNER JOIN Value V
ON E.CaseNum = V.CaseNum AND
    E.FileNum = V.FileNum AND 
    E.ActivityNum = V.ActivityNum

Create table

CREATE TABLE MyNewTab(CaseNum int, FileNum int,
    ActivityNum int, Grade int, Score varchar(100))

Insert values

INSERT INTO MyNewTab Values(CaseNum, FileNum, ActivityNum, Grade, Score)
SELECT E.CaseNum, E.FileNum, E.ActivityNum, E.Grade, V.Score from Evaluation E
INNER JOIN Value V
ON E.CaseNum = V.CaseNum AND
    E.FileNum = V.FileNum AND 
    E.ActivityNum = V.ActivityNum

pandas: merge (join) two data frames on multiple columns

Try this

new_df = pd.merge(A_df, B_df,  how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.merge.html

left_on : label or list, or array-like Field names to join on in left
DataFrame. Can be a vector or list of vectors of the length of the
DataFrame to use a particular vector as the join key instead of
columns

right_on : label or list, or array-like Field names to join on
in right DataFrame or vector/list of vectors per left_on docs

join on multiple columns

Agree no matches in your example.

If you mean both columns on either then need a query like this or need to re-examine the data design.

    Select TableA.Col1, TableA.Col2, TableB.Val
    FROM TableA
    INNER JOIN TableB
          ON TableA.Col1 = TableB.Col1 OR TableA.Col2 = TableB.Col2 
          OR TableA.Col2 = TableB.Col1 OR TableA.Col1 = TableB.Col2

Efficient way to join multiple columns to the same column? - SQL

You might find it easier to use a correlated subquery for each username, especially where you have to implement many columns as it's easier to cut n paste!

Something like:

select 
 (select Username from Mapping m where m.UserId = t.UserId1) Username1,
 (select Username from Mapping m where m.UserId = t.UserId2) Username2,
 (select Username from Mapping m where m.UserId = t.UserId3) Username3 etc
from InputTable t

How to do an INNER JOIN on multiple columns

You can JOIN with the same table more than once by giving the joined tables an alias, as in the following example:

SELECT 
    airline, flt_no, fairport, tairport, depart, arrive, fare
FROM 
    flights
INNER JOIN 
    airports from_port ON (from_port.code = flights.fairport)
INNER JOIN
    airports to_port ON (to_port.code = flights.tairport)
WHERE 
    from_port.code = '?' OR to_port.code = '?' OR airports.city='?'

Note that the to_port and from_port are aliases for the first and second copies of the airports table.

SQL left outer join on multiple columns

That depends on whether the columns are nullable, but assuming they are not, checking any of them will do:

SELECT *
  FROM a
  LEFT JOIN b 
    ON  a.foo = b.foo
    AND a.bar = b.bar
    AND a.ter = b.ter
WHERE b.foo IS NULL -- this could also be bar or ter

This is because after a successful join, all three columns will have a non-null value.

If some of these columns were nullable and you'd like to check if any one of them had a value after the join, then your first (OR) approach would be OK.

SQL join on multiple columns in same tables?

You can implement it as a JOIN with two independent JOINs to CODE_TABLE, one for each value in DATA_TABLE:

SELECT A.COLUMN1,
       B1.CODE_NAME AS COLUMN2,
       B2.CODE_NAME AS COLUMN3
FROM DATA_TABLE A
JOIN CODE_TABLE B1 ON B1.CODE = A.COLUMN2
JOIN CODE_TABLE B2 ON B2.CODE = A.COLUMN3

If it's possible that a value from COLUMN2 or COLUMN3 in DATA_TABLE might not exist in CODE_TABLE, you should use LEFT JOIN instead, and COALESCE on the output so as not to return a NULL value:

SELECT A.COLUMN1,
       COALESCE(B1.CODE_NAME, '') AS COLUMN2,
       COALESCE(B2.CODE_NAME, '') AS COLUMN3
FROM DATA_TABLE A
LEFT JOIN CODE_TABLE B1 ON B1.CODE = A.COLUMN2
LEFT JOIN CODE_TABLE B2 ON B2.CODE = A.COLUMN3

Output (for your sample data)

COLUMN1 COLUMN2 COLUMN3
test    APPLE   LG
test1   SAMSUNG HWAWEI
test2   OPPO    GOOGLE

Demo on dbfiddle

---

Related Topics