datascience.tables.Table.join

Table.join(column_label, other, other_label=None)

Creates a new table with the columns of self and other, containing rows for all values of a column that appear in both tables.

Args:

column_label (str): label of column in self that is used to

join rows of other.

other: Table object to join with self on matching values of

column_label.

Kwargs:

other_label (str): default None, assumes column_label.

Otherwise in other used to join rows.

Returns:

New table self joined with other by matching values in column_label and other_label. If the resulting join is empty, returns None. If a join value appears more than once in self, each row with that value will appear in resulting join, but in other, only the first row with that value will be used.

>>> table = Table().with_columns('a', make_array(9, 3, 3, 1),
...     'b', make_array(1, 2, 2, 10),
...     'c', make_array(3, 4, 5, 6))
>>> table
a    | b    | c
9    | 1    | 3
3    | 2    | 4
3    | 2    | 5
1    | 10   | 6
>>> table2 = Table().with_columns( 'a', make_array(9, 1, 1, 1),
... 'd', make_array(1, 2, 2, 10),
... 'e', make_array(3, 4, 5, 6))
>>> table2
a    | d    | e
9    | 1    | 3
1    | 2    | 4
1    | 2    | 5
1    | 10   | 6
>>> table.join('a', table2)
a    | b    | c    | d    | e
1    | 10   | 6    | 2    | 4
9    | 1    | 3    | 1    | 3
>>> table.join('a', table2, 'a') # Equivalent to previous join
a    | b    | c    | d    | e
1    | 10   | 6    | 2    | 4
9    | 1    | 3    | 1    | 3
>>> table.join('a', table2, 'd') # Repeat column labels relabeled
a    | b    | c    | a_2  | e
1    | 10   | 6    | 9    | 3
>>> table2 #table2 has three rows with a = 1
a    | d    | e
9    | 1    | 3
1    | 2    | 4
1    | 2    | 5
1    | 10   | 6
>>> table #table has only one row with a = 1
a    | b    | c
9    | 1    | 3
3    | 2    | 4
3    | 2    | 5
1    | 10   | 6
>>> table2.join('a', table) # When we join, we get all three rows in table2 where a = 1
a    | d    | e    | b    | c
1    | 2    | 4    | 10   | 6
1    | 2    | 5    | 10   | 6
1    | 10   | 6    | 10   | 6
9    | 1    | 3    | 1    | 3
>>> table.join('a', table2) # Opposite join only keeps first row in table2 with a = 1
a    | b    | c    | d    | e
1    | 10   | 6    | 2    | 4
9    | 1    | 3    | 1    | 3