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The join() method of Array instances creates and returns a new string by concatenating all of the elements in this array, separated by commas or a specified separator string. If the array has only one item, then that item will be returned without using the separator.
Array.prototype.join recursively converts each element, including other arrays, to strings. Because the string returned by Array.prototype.toString (which is the same as calling join()) does not have delimiters, nested arrays look like they are flattened. You can only control the separator of the first level, while deeper levels always use the default comma.
\n The join() method of Array instances creates and\n returns a new string by concatenating all of the elements in this array,\n separated by commas or a specified separator string. If the array has\n only one item, then that item will be returned without using the separator.\n
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Column or index level name(s) in the caller to join on the indexin other, otherwise joins index-on-index. If multiplevalues given, the other DataFrame must have a MultiIndex. Canpass an array as the join key if it is not already contained inthe calling DataFrame. Like an Excel VLOOKUP operation.
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if concatenating bytes objects, you can similarly usebytes.join() or io.BytesIO, or you can do in-placeconcatenation with a bytearray object. bytearrayobjects are mutable and have an efficient overallocation mechanism
The subset and equality comparisons do not generalize to a total orderingfunction. For example, any two nonempty disjoint sets are not equal and are notsubsets of each other, so all of the following return False: ab.
A join clause in the Structured Query Language (SQL) combines columns from one or more tables into a new table. The operation corresponds to a join operation in relational algebra. Informally, a join stitches two tables and puts on the same row records with matching fields : INNER, LEFT OUTER, RIGHT OUTER, FULL OUTER and CROSS.
CROSS JOIN does not itself apply any predicate to filter rows from the joined table. The results of a CROSS JOIN can be filtered using a WHERE clause, which may then produce the equivalent of an inner join.
An inner join (or join) requires each row in the two joined tables to have matching column values, and is a commonly used join operation in applications but should not be assumed to be the best choice in all situations. Inner join creates a new result table by combining column values of two tables (A and B) based upon the join-predicate. The query compares each row of A with each row of B to find all pairs of rows that satisfy the join-predicate. When the join-predicate is satisfied by matching non-NULL values, column values for each matched pair of rows of A and B are combined into a result row.
The result of the join can be defined as the outcome of first taking the cartesian product (or cross join) of all rows in the tables (combining every row in table A with every row in table B) and then returning all rows that satisfy the join predicate. Actual SQL implementations normally use other approaches, such as hash joins or sort-merge joins, since computing the Cartesian product is slower and would often require a prohibitively large amount of memory to store.
SQL specifies two different syntactical ways to express joins: the "explicit join notation" and the "implicit join notation". The "implicit join notation" is no longer considered a best practice[by whom?], although database systems still support it.
The "explicit join notation" uses the JOIN keyword, optionally preceded by the INNER keyword, to specify the table to join, and the ON keyword to specify the predicates for the join, as in the following example:
The "implicit join notation" simply lists the tables for joining, in the FROM clause of the SELECT statement, using commas to separate them. Thus it specifies a cross join, and the WHERE clause may apply additional filter-predicates (which function comparably to the join-predicates in the explicit notation).
The queries given in the examples above will join the Employee and department tables using the DepartmentID column of both tables. Where the DepartmentID of these tables match (i.e. the join-predicate is satisfied), the query will combine the LastName, DepartmentID and DepartmentName columns from the two tables into a result row. Where the DepartmentID does not match, no result row is generated.
The employee "Williams" and the department "Marketing" do not appear in the query execution results. Neither of these has any matching rows in the other respective table: "Williams" has no associated department, and no employee has the department ID 35 ("Marketing"). Depending on the desired results, this behavior may be a subtle bug, which can be avoided by replacing the inner join with an outer join.
Programmers should take special care when joining tables on columns that can contain NULL values, since NULL will never match any other value (not even NULL itself), unless the join condition explicitly uses a combination predicate that first checks that the joins columns are NOT NULL before applying the remaining predicate condition(s). The Inner Join can only be safely used in a database that enforces referential integrity or where the join columns are guaranteed not to be NULL. Many transaction processing relational databases rely on atomicity, consistency, isolation, durability (ACID) data update standards to ensure data integrity, making inner joins an appropriate choice. However, transaction databases usually also have desirable join columns that are allowed to be NULL. Many reporting relational database and data warehouses use high volume extract, transform, load (ETL) batch updates which make referential integrity difficult or impossible to enforce, resulting in potentially NULL join columns that an SQL query author cannot modify and which cause inner joins to omit data with no indication of an error. The choice to use an inner join depends on the database design and data characteristics. A left outer join can usually be substituted for an inner join when the join columns in one table may contain NULL values.
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