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Columns

How to manipulate columns

Commands(s) Operation
! pins the current column on the left as a key column
H L slides the current column one position to the left/right
gH gL slides the current column all the way to the left/right of its section

How to hide (remove) and unhide (return) columns

How to hide columns
  • Press - (hyphen) to hide the current column.

or

  1. Press Shift+C on the source sheet to open its Columns sheet.
  2. Move the cursor right to the width column.
  3. Move the cursor down to the row which represents the column you wish to hide.
  4. Press e followed by 0 to set the width for that column to 0.
  5. Press q to return to the source sheet.
How to unhide columns
  1. Press gv to unhide all columns on current sheet.

or

  1. Press Shift+C on the source sheet to open its Columns sheet.
  2. Move the cursor right to the width column.
  3. Move the cursor down to the row which represents the column you wish to unhide. Currently, that cell should contain the value 0.
  4. Press e followed by a positive number to set the width.
  5. Press q to return to the source sheet.

How to specify column types

Command Type
~ string
# int
% float
$ currency
@ date
z# vlen
z~ anytype

Columns usually begin as untyped. Odd results while working with numerical or datetime data is usually due to values being considered as strings, and the problem is solved by setting the correct type.

The float type uses Python's builtin float() constructor to parse the string, and it parses by using the decimal separator.

The currency type is a bit of a misnomer. It filters out any non-numeric characters, and then parses the remainder of the cell value as a float. The reasons to prefer using float over currency, is performance (it is quite a bit slower than native parsing with float), or if any non-float characters should get reported as an error.

The date type parses dates into ISO8601 format. Those columns can then be used in mathematical calculations, and the calculations are interpreted for dates. E.g. 2020-01-01 + 1, is 2020-01-02.

The vlen type formats the cell value to the length of the content. For example, if the cell content is a list of length 3, then when vlen typed it will display a value of 3.

There is also the floatlocale type, which uses Python's locale.atof to parse the Column values. With floatlocale, you can set the LC_NUMERIC environment variable appropriately (before launching VisiData), such that atof() will parse the number based on your locale setting. There is a type-floatlocale command, which is unbound by default, because parsing this way is significantly slower than using the builtin float type.

If you need locale-specific float parsing regularly, you may want to rebind % or z% (or maybe some other keystroke) to type-floatlocale instead.

The following example uses the file sample.tsv.

How to batch specify column types for more than one column
  1. Press Shift+C to open the Columns sheet.
  2. Press s or t to select the rows referencing the columns you wish to type.
  3. Type g followed by the any of the above typing keystrokes to set the type for all selected columns on the source sheet.

How to format columns

Note: Un-typed file formats, like tsvs and csvs, will save as they are displayed.

Some types have an option for their default display formatting.

Type Option Default
int dispintfmt {:.0f}
float dispfloatfmt {:.02f}
currency dispcurrencyfmt %0.2f
date dispdatefmt %Y-%m-%d

Ways to adjust the display formatting:

  • The fmtstr column on the Columns Sheet allows you to specify the formatting for specific columns within that session, without affecting the default for the others.
  • The disp_TYPE_fmt option can be changed on the Options Sheet to set the formatting for all columns of type TYPE in that session.
  • The --disp-TYPE-fmt argument can be passed through the commandline to set the formatting for all columns of type TYPE in that session.
  • The options.disp_TYPE_fmt can be set in the ~/.visidatarc to change the default formatting for all columns of type TYPE for all sessions.

There are several formatting styles offered:

The default for currency uses locale.format_string(). The default for int/float/date use string.format().

How to format a specific numeric columns to contain a thousands separator within a session?
  1. Set a column to a numeric type by pressing # (int), % (float), or $ (currency).
  2. Press Shift+C to open the Columns Sheet.
  3. Move to the row referencing the column whose display you wish to format. Move the cursor to the fmtstr column.
  4. Type e followed by {:,.0f} for an int type and {:,.02f} for a floating point type.
How to set all date columns to be month/day/year.

The default can be set in a ~/.visidatarc.

options.disp_date_fmt = '%m/%d/%Y'

or passed through the commandline

vd --disp-date-fmt='%m/%d/%Y'

or set in the Options Sheet.

  1. Press Shift+O to open the Options Sheet.
  2. Move the cursor down to the relevant dispdatefmt option.
  3. Type e followed by %m/%d/%Y.

How to specify a comma decimal separator when typing floating point numbers?
  1. Before launching VisiData, set the shell environment variable LC_NUMERIC to a locale which interprets commas as decimals. Any European locale should do; an example that works is en_DK.UTF-8.
  2. Within VisiData, set a column to type floatlocale by pressing Space followed by type-floatlocale.

Note that type-floatlocale is significantly slower than type-float. However, if you wish to replace the current binding for type-float with type-floatlocale, add to your ~/.visidatarc:

Sheet.unbindkey('%')
Sheet.bindkey('%', 'type-floatlocale')

or if you never use type-floatsi, you can do

Sheet.unbindkey('z%')
Sheet.bindkey('z%', 'type-floatlocale')

How to split a column

Python regular expressions provide more finetuned column splitting. The following example uses the commands for column splitting and transformation with xd/puzzles.tsv.

  • : adds new columns derived from splitting the current column at positions defined by a regex pattern. The current row will be used to infer the number of columns that will be created.
  • ; adds new columns derived from pulling the contents of the current column which match the regex within capture groups. The new columns are named using the capture group index, or if named capture groups are used, the capture group names. This command also requires an example row.
  • * followed by regex/substring replaces the text which matches the capture groups in regex with the contents of substring. substring may include backreferences (\1 etc).

[How do I substitute text in my column]

The * command can be used to do content transformations of cells. The g* variant transforms in-place, instead of creating a new column.

The following example uses benchmarks.csv.

Question Transform the SKU values of food to nutri.

  1. Move cursor to SKU column.
  2. Press gs to select all rows.
  3. Type g* folowed by food/nutri.
  • tests/transform-cols.vd

How to expand columns that contain nested data

If a column includes container data such as JSON objects or arrays, the ( family of commands can expand the child values into top-level columns:

Command Operation
( expand current column
g( expand all visible columns fully
z( expand current column to a specific depth (prompt for input)
gz( expand all visible columns to a specific depth (prompt for input)
) contract (unexpand) the current column

The following demo shows ( commands applied to this data:

[
    [ "short", "array" ],
    [ "slightly", "longer", "array" ],
    { "nested": "data" },
    { "more": { "deeply": { "nested": "data" } } }
]

Note that by default the expansion logic will look for nested columns in up to 1,000 rows surrounding the cursor. This behavior can be controlled by adjusting expand_col_scanrows in the Options Sheet, or setting options.expand_col_scanrows in the ~/.visidatarc file.


How to create derivative columns

The = command takes a Python expression as input and creates a new column, where each cell evaluates the expression in the context of its row.

These variables and functions are available in the scope of an expression:

  • Column names evaluate to the typed value of the cell in the named column for the same row.
  • vd attributes and methods; use Ctrl+X vd to view the vd object, or see the API.
  • Sheet attributes and methods; use g Ctrl+Y to view the sheet object (or see the API).
  • Global functions and variables (add your own in your .visidatarc).
  • modules that have been imported in Python
    • if you need a module that hasn't already been imported at runtime, use g Ctrl+X import <modname>.
  • sheet: the current sheet (a TableSheet object)
  • col: the current column (as a Column object; use for Column metadata)
  • row: the current row (a Python object of the internal rowtype)
  • curcol: evaluate to the typed value of this row in the column that the cursor was on at the time that the expression column was added.
  • cursorCol: evaluate to the typed value of this row for the column the cursor is on. Changes as the cursor moves for =. Uses the column from the time the calculation was made for g=, gz=, and z=.

Additional attributes can be added to sheets and columns.

col deliberately returns a Column object, but any other Column object is interpreted as the value within that column for the same row. For example, both curcol and cursorcol return values, not the object itself.

For example, this customizes addcol-expr to set the curcol attribute on the new ExprColumn to a snapshot of the current cursor column (at the time the expression column is added):

Sheet.addCommand('=', 'addcol-expr', 'addColumnAtCursor(ExprColumn(inputExpr("new column expr="), curcol=cursorCol))', 'create new column from Python expression, with column names as variables')

Then, an expression can use curcol as though it referred to the value in the saved column.

Tab autocompletion when inputting an expression will cycle through valid column names only.

The following examples use the file sample.tsv.

Question On which days have we sold more than 10 Items?

  1. Scroll to the Units column. Set the type of the Units column by pressing # (int).
  2. Type = followed by Units > 10. A new column will be created. The cells in this column will contain the value True in rows where the number of Units are greater than 10 and False otherwise.
  3. Move to the new derived column.
  4. Type | followed by True to select all rows where there were more than 10 Units sold.
  5. Press " to open a duplicate sheet with only those selected rows.

Question I have a dateset with separate columns for Year, Month and Day. How can I concatenate them into a single date column?

  1. Type = followed by Year + '-' + Month + '-' + Day.
  2. Set the type of the new derived column by pressing @ (date).
  3. Type ^ followed by Date to rename the column to Date.

Question I have a dataset with Date column that is missing a prefix of '2020-'. How do I add it to the Date column?

When using =, and wanting to reference the current column, we recommend using curcol. When using g=, gz=, and z=, we recommend cursorCol. =, unlike the others, is dynamic and changes with adjustment of underlying values, which means it will change along with the movement of the cursor (tracked by cursorCol). curcol is a special attribute of a new ExprColumn, which remembers the cursorCol at the time of creation.

  1. Move the cursor to Date.
  2. Type g= followed by f"2020-{cursorCol}".

Question I have a dataset with file names. How do I create a new column with the file names lower cased?

  1. Move the cursor to file names column.
  2. Type = followed by curcol.casefold().
  3. Move to the newly created column, and rename it with ^, followed by the desired name.

How to configure multiple columns

Properties of columns on the source sheet can be changed by using standard editing commands on its Columns sheet (accessed with Shift+C). In particular, it facilitates the selection of multiple columns, followed by utilising one of the g-prefixed commands to modify all of them.

For a full list of available commands, see the man page. Some example workflows follow.

The following examples use the file sample.tsv.

How to set multiple statistical aggregators

Question What is the average daily revenue from sales of each Item?

  1. Set the type of the Units column by pressing # (int).
  2. Set the type of the Total column by pressing % (float).
  3. Press Shift+C to open the Columns sheet.
  4. Press s or t on the rows referencing the source sheet Units column and the Total column to select them.
  5. Type g+ followed by avg to add a avg statistical aggregator to the selected rows.
  6. Press q to exit and return to the source sheet.
  7. Scroll to the Item column. Press Shift+F to open the Frequency table.

Question What are the daily average and sum total number of Units sold for each Item?

  1. Press Shift+C to open the Columns sheet.
  2. Move the cursor to the row referencing the source sheet Units column.

    a. Press s or t to select it. b. Set the type for the source sheet Units columns by pressing g# (int). c. Move the cursor to the aggregators column.

    d. Type e to enter edit mode, followed by sum avg.

  3. Press q to exit and return to the source sheet.
  4. Move the cursor to the Item column. Press Shift+F to open the Frequency table.


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