README.md

dfsql

• Revision: the standalone count command is replaced with len, so make sure to replace (count) and col "count" with len and col "len" respectively.
  • the unary count <col> command is unaffected.

Install

cargo install dfsql

How to run

dfsql --input your.csv --output a-new.csv
# ...or
dfsql -i your.csv -o a-new.csv

REPL

• exit/quit: exit the REPL loop.

  exit

• undo: undo the previous successful operation.

  undo

• reset: reset all the changes and go back to the original data frame.

  reset

• schema: show column names and types of the data frame.

  schema

• save: save the current data frame to a file.

  save a-new.csv

Statements

• select

  select <expr>*

  select last_name first_name

  • Select columns "last_name" and "first_name" and collect them into a data frame.
• Group by

  group (<col> | <var>)* agg <expr>*

  group first_name agg (count)

  • Group the data frame by column "first_name" and then aggregate each group with the count of the members.
• filter

  filter <expr>

  filter first_name = "John"

• limit

  limit <int>

  limit 5

• reverse

  reverse

• sort

  sort ((asc | desc | ()) <col>)*

  sort icpsr_id

• use

  use <var>

  use other

  • Switch to the data frame called other.
• join

  (left | right | inner | full) join <var> on <col> <col>?

  left join other on id ID

  • left join the data frame called other on my column id and its column ID

Expressions

• col: reference to a column.

  col : (<str> | <var>) -> <expr>

  select col first_name

• exclude: remove columns from the data frame.

  exclude : <expr>* -> <expr>

  select exclude last_name first_name

• literal: literal values like 42, "John", 1.0, and null.
• binary operations

  select a * b

  • Calculate the product of columns "a" and "b" and collect the result.
• unary operations

  select -a

  select sum a

  • Sum all values in column "a" and collect the scalar result.
• alias: assign a name to a column.

  alias : (<col> | <var>) <expr> -> <expr>

  select alias product a * b

  • Assign the name "product" to the product and collect the new column.
• conditional

  <conditional> : if <expr> then <expr> (if <expr> then <expr>)* otherwise <expr> -> <expr>

  select if class = 0 then "A" if class = 1 then "B" else null

• cast: cast a column to either type str, int, or float.

  cast : <type> <expr> -> <expr>

  select cast str id

  • Cast the column "id" to type str and collect the result.