PSA: Literally none of this has been implemented
Read from CSV:
(table-from-csv "foo.csv")Read from SQL:
(table-from-sql "select foo, bar from baztable;" sqlconn)Take n values from table
(take table 10)Slice table
(slice table 5 10)Get distinct values for given columns (or the whole table)
;; Returns a new table (two cols wide) with distinct values from col1 and col2
(distinct table [:col1 :col2])
;; Returns distinct (unique) rows for the entire table
(distinct table)Sort values for given vector of cols
(sort table {:col1 #(sortfunc)} :type :asc])Filter values where a predicate is matched
(filter table {:col1 #(= % "foo") :col2 #{1 2}})Apply a function on columns
(apply table {:col1 #(* 4 %) :col2 #(str % "_appender")})Potentially: Apply a function with logic on multiple cols (apply (fn :col1 :col2))
Reduce columns
;; This will probably return a map of {:col reduced_value}?
(reduce table {:col1 + :col2 #(+ %1 %2 2)})Select columns
(select table [:col1 :col2])Group a table. This will return a map of group keys to...new tables?
(groupby table [:col1])
{:foo-group <Table> :bar-group <Table>}Join two tables
(left-join table1 table2 :on [:col1])
(right-join table1 table2 :on [:col1])
(inner-join table1 table2 :on [:col1 :col2])
(outer-join table1 table2 :on [:col2])Set operations
(intersect table1 table2)
(union table1 table2)
(diff table1 table2)Compose a pipeline of operations:
(c<- table
(filter {:col1 #{1}})
(groupby [:col2])
(reduce {:col1 +}))Equivalent to
select sum(col1)
from table
where col1 = 1
groupby col2;