A CSV::Table is a two-dimensional data structure for representing CSV documents. Tables allow you to work with the data by row or column, manipulate the data, and even convert the results back to CSV, if needed.

All tables returned by CSV will be constructed from this class, if header row processing is activated.


Class Methods


Constructs a new CSV::Table from array_of_rows, which are expected to be CSV::Row objects. All rows are assumed to have the same headers.

The optional headers parameter can be set to Array of headers. If headers aren't set, headers are fetched from CSV::Row objects. Otherwise, headers() method will return headers being set in headers argument.

A CSV::Table object supports the following Array methods through delegation:

  • empty?()

  • length()

  • size()

Instance Methods


If row_or_array is a CSV::Row object, it is appended to the table:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table << CSV::Row.new(table.headers, ['bat', 3])
table[3] # => #<CSV::Row "Name":"bat" "Value":3>

If row_or_array is an Array, it is used to create a new CSV::Row object which is then appended to the table:

table << ['bam', 4]
table[4] # => #<CSV::Row "Name":"bam" "Value":4>

Returns true if all each row of self == the corresponding row of other_table, otherwise, false.

The access mode does no affect the result.

Equal tables:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
other_table = CSV.parse(source, headers: true)
table == other_table # => true

Different row count:

other_table.delete(2)
table == other_table # => false

Different last row:

other_table << ['bat', 3]
table == other_table # => false

Returns data from the table; does not modify the table.


The expression table[n], where n is a non-negative Integer, returns the +n+th row of the table, if that row exists, and if the access mode is :row or :col_or_row:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.by_row! # => #<CSV::Table mode:row row_count:4>
table[1] # => #<CSV::Row "Name":"bar" "Value":"1">
table.by_col_or_row! # => #<CSV::Table mode:col_or_row row_count:4>
table[1] # => #<CSV::Row "Name":"bar" "Value":"1">

Counts backward from the last row if n is negative:

table[-1] # => #<CSV::Row "Name":"baz" "Value":"2">

Returns nil if n is too large or too small:

table[4] # => nil
table[-4] => nil

Raises an exception if the access mode is :row and n is not an Integer-convertible object.

table.by_row! # => #<CSV::Table mode:row row_count:4>
# Raises TypeError (no implicit conversion of String into Integer):
table['Name']

The expression table[range], where range is a Range object, returns rows from the table, beginning at row range.first, if those rows exist, and if the access mode is :row or :col_or_row:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.by_row! # => #<CSV::Table mode:row row_count:4>
rows = table[1..2] # => #<CSV::Row "Name":"bar" "Value":"1">
rows # => [#<CSV::Row "Name":"bar" "Value":"1">, #<CSV::Row "Name":"baz" "Value":"2">]
table.by_col_or_row! # => #<CSV::Table mode:col_or_row row_count:4>
rows = table[1..2] # => #<CSV::Row "Name":"bar" "Value":"1">
rows # => [#<CSV::Row "Name":"bar" "Value":"1">, #<CSV::Row "Name":"baz" "Value":"2">]

If there are too few rows, returns all from range.first to the end:

rows = table[1..50] # => #<CSV::Row "Name":"bar" "Value":"1">
rows # => [#<CSV::Row "Name":"bar" "Value":"1">, #<CSV::Row "Name":"baz" "Value":"2">]

Special case: if range.start == table.size, returns an empty Array:

table[table.size..50] # => []

If range.end is negative, calculates the ending index from the end:

rows = table[0..-1]
rows # => [#<CSV::Row "Name":"foo" "Value":"0">, #<CSV::Row "Name":"bar" "Value":"1">, #<CSV::Row "Name":"baz" "Value":"2">]

If range.start is negative, calculates the starting index from the end:

rows = table[-1..2]
rows # => [#<CSV::Row "Name":"baz" "Value":"2">]

If range.start is larger than table.size, returns nil:

table[4..4] # => nil

The expression table[header], where header is a String, returns column values (Array of Strings) if the column exists and if the access mode is :col or :col_or_row:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.by_col! # => #<CSV::Table mode:col row_count:4>
table['Name'] # => ["foo", "bar", "baz"]
table.by_col_or_row! # => #<CSV::Table mode:col_or_row row_count:4>
col = table['Name']
col # => ["foo", "bar", "baz"]

Modifying the returned column values does not modify the table:

col[0] = 'bat'
col # => ["bat", "bar", "baz"]
table['Name'] # => ["foo", "bar", "baz"]

Returns an Array of nil values if there is no such column:

table['Nosuch'] # => [nil, nil, nil]

In the default mixed mode, this method assigns rows for index access and columns for header access. You can force the index association by first calling by_col!() or by_row!().

Rows may be set to an Array of values (which will inherit the table's headers()) or a CSV::Row.

Columns may be set to a single value, which is copied to each row of the column, or an Array of values. Arrays of values are assigned to rows top to bottom in row major order. Excess values are ignored and if the Array does not have a value for each row the extra rows will receive a nil.

Assigning to an existing column or row clobbers the data. Assigning to new columns creates them at the right end of the table.

Returns a duplicate table object, in column mode. This is handy for chaining in a single call without changing the table mode, but be aware that this method can consume a fair amount of memory for bigger data sets.

This method returns the duplicate table for chaining. Don't chain destructive methods (like []=()) this way though, since you are working with a duplicate.

Switches the mode of this table to column mode. All calls to indexing and iteration methods will work with columns until the mode is changed again.

This method returns the table and is safe to chain.

Returns a duplicate table object, in mixed mode. This is handy for chaining in a single call without changing the table mode, but be aware that this method can consume a fair amount of memory for bigger data sets.

This method returns the duplicate table for chaining. Don't chain destructive methods (like []=()) this way though, since you are working with a duplicate.

Switches the mode of this table to mixed mode. All calls to indexing and iteration methods will use the default intelligent indexing system until the mode is changed again. In mixed mode an index is assumed to be a row reference while anything else is assumed to be column access by headers.

This method returns the table and is safe to chain.

Returns a duplicate table object, in row mode. This is handy for chaining in a single call without changing the table mode, but be aware that this method can consume a fair amount of memory for bigger data sets.

This method returns the duplicate table for chaining. Don't chain destructive methods (like []=()) this way though, since you are working with a duplicate.

Switches the mode of this table to row mode. All calls to indexing and iteration methods will work with rows until the mode is changed again.

This method returns the table and is safe to chain.

If the access mode is :row or :col_or_row, and each argument is either an Integer or a Range, returns deleted rows. Otherwise, returns deleted columns data.

In either case, the returned values are in the order specified by the arguments. Arguments may be repeated.


Returns rows as an Array of CSV::Row objects.

One index:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
deleted_values = table.delete(0)
deleted_values # => [#<CSV::Row "Name":"foo" "Value":"0">]

Two indexes:

table = CSV.parse(source, headers: true)
deleted_values = table.delete(2, 0)
deleted_values # => [#<CSV::Row "Name":"baz" "Value":"2">, #<CSV::Row "Name":"foo" "Value":"0">]

Returns columns data as column Arrays.

One header:

table = CSV.parse(source, headers: true)
deleted_values = table.delete('Name')
deleted_values # => ["foo", "bar", "baz"]

Two headers:

table = CSV.parse(source, headers: true)
deleted_values = table.delete('Value', 'Name')
deleted_values # => [["0", "1", "2"], ["foo", "bar", "baz"]]

Removes rows or columns for which the block returns a truthy value; returns self.

Removes rows when the access mode is :row or :col_or_row; calls the block with each CSV::Row object:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.by_row! # => #<CSV::Table mode:row row_count:4>
table.size # => 3
table.delete_if {|row| row['Name'].start_with?('b') }
table.size # => 1

Removes columns when the access mode is :col; calls the block with each column as a 2-element array containing the header and an Array of column fields:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.by_col! # => #<CSV::Table mode:col row_count:4>
table.headers.size # => 2
table.delete_if {|column_data| column_data[1].include?('2') }
table.headers.size # => 1

Returns a new Enumerator if no block is given:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.delete_if # => #<Enumerator: #<CSV::Table mode:col_or_row row_count:4>:delete_if>

Extracts the nested value specified by the sequence of index or header objects by calling dig at each step, returning nil if any intermediate step is nil.

Calls the block with each row or column; returns self.

When the access mode is :row or :col_or_row, calls the block with each CSV::Row object:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.by_row! # => #<CSV::Table mode:row row_count:4>
table.each {|row| p row }

Output:

#<CSV::Row "Name":"foo" "Value":"0">
#<CSV::Row "Name":"bar" "Value":"1">
#<CSV::Row "Name":"baz" "Value":"2">

When the access mode is :col, calls the block with each column as a 2-element array containing the header and an Array of column fields:

table.by_col! # => #<CSV::Table mode:col row_count:4>
table.each {|column_data| p column_data }

Output:

["Name", ["foo", "bar", "baz"]]
["Value", ["0", "1", "2"]]

Returns a new Enumerator if no block is given:

table.each # => #<Enumerator: #<CSV::Table mode:col row_count:4>:each>

Returns the headers for the first row of this table (assumed to match all other rows). The headers Array passed to CSV::Table.new is returned for empty tables.

Shows the mode and size of this table in a US-ASCII String.

A shortcut for appending multiple rows. Equivalent to:

rows.each {|row| self << row }

Each argument may be either a CSV::Row object or an Array:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
rows = [
  CSV::Row.new(table.headers, ['bat', 3]),
  ['bam', 4]
]
table.push(*rows)
table[3..4] # => [#<CSV::Row "Name":"bat" "Value":3>, #<CSV::Row "Name":"bam" "Value":4>]

Returns the table as an Array of Arrays. Headers will be the first row, then all of the field rows will follow.

Returns the table as a complete CSV String. Headers will be listed first, then all of the field rows.

This method assumes you want the Table.headers(), unless you explicitly pass :write_headers => false.

If the access mode is :row or :col_or_row, and each argument is either an Integer or a Range, returns rows. Otherwise, returns columns data.

In either case, the returned values are in the order specified by the arguments. Arguments may be repeated.


Returns rows as an Array of CSV::Row objects.

No argument:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
table = CSV.parse(source, headers: true)
table.values_at # => []

One index:

values = table.values_at(0)
values # => [#<CSV::Row "Name":"foo" "Value":"0">]

Two indexes:

values = table.values_at(2, 0)
values # => [#<CSV::Row "Name":"baz" "Value":"2">, #<CSV::Row "Name":"foo" "Value":"0">]

One Range:

values = table.values_at(1..2)
values # => [#<CSV::Row "Name":"bar" "Value":"1">, #<CSV::Row "Name":"baz" "Value":"2">]

Ranges and indexes:

values = table.values_at(0..1, 1..2, 0, 2)
pp values

Output:

[#<CSV::Row "Name":"foo" "Value":"0">,
 #<CSV::Row "Name":"bar" "Value":"1">,
 #<CSV::Row "Name":"bar" "Value":"1">,
 #<CSV::Row "Name":"baz" "Value":"2">,
 #<CSV::Row "Name":"foo" "Value":"0">,
 #<CSV::Row "Name":"baz" "Value":"2">]

Returns columns data as row Arrays, each consisting of the specified columns data for that row:

values = table.values_at('Name')
values # => [["foo"], ["bar"], ["baz"]]
values = table.values_at('Value', 'Name')
values # => [["0", "foo"], ["1", "bar"], ["2", "baz"]]