Table: {csv_filename}

Query data from CSV files. A table is automatically created to represent each CSV file found in the configured paths.

For instance, if paths is set to /Users/myuser/csv/*, and that directory contains:

• products.csv
• users.csv

This plugin will create 2 tables:

• products
• users

Which you can then query directly:

select
  *
from
  users;

Each of these tables will have the same column structure as the CSV they were created from and all column values are returned as text data type.

Examples

Inspect the table structure

Assuming your connection is called csv (the default), list all tables with:

.inspect csv
+----------+--------------------------------------------+
| table    | description                                |
+----------+--------------------------------------------+
| products | CSV file at /Users/myuser/csv/products.csv |
| users    | CSV file at /Users/myuser/csv/users.csv    |
+----------+--------------------------------------------+

To get defails for a specific table, inspect it by name:

.inspect csv.users
+------------+------+-------------+
| column     | type | description |
+------------+------+-------------+
| first_name | text | Field 0.    |
| last_name  | text | Field 1.    |
| email      | text | Field 2.    |
+------------+------+-------------+

Query a simple file

Given the file users.csv, the query is:

select
  *
from
  users;

Query a complex file name

Given the file My complex file-name.csv, the query uses identifier quotes:

select
  *
from
  "My complex file-name"

Query specific columns

Columns are always in text form when read from the CSV file. The column names come from the first row of the file.

select
  first_name,
  last_name
from
  users

If your column names are complex, use identifier quotes:

select
  "First Name",
  "Last Name"
from
  users

Casting column data for analysis

Text columns can be easily cast to other types:

select
  first_name,
  age::int as iage
from
  users
where
  iage > 25