class Dataframe

• Dataframe
• Reference
• Object

Overview

NOTE The CSV Spec(RFC 4180) does state that leading and trailing whitespaces should not be ignored, some implementations of CSV do still use them. For this reason, Dataframe will ignore leading and trailing whitespace in unquoted cells.

Defined in:

Constant Summary

VERSION = "0.1.0"

Constructors

• .from_csv(string_or_io : String | IO, headers : Bool = true, separator : Char = CSVLexer::DEFAULT_SEPARATOR, quote_char : Char = CSVLexer::DEFAULT_QUOTE_CHAR) : Dataframe
• .new(headers : Array(String), rows : Array(Array(Type)))

  Creates a new Dataframe instance with the given headers and rows.

• .new(column_names : Array(String))

  Creates a new Dataframe instance with the specified headers, and columns of type String, but with no data.

• .new(columns)

  Creates a new Dataframe instance with column names and types defined by columns, but with no data.

• .new

  Creates an empty Dataframe instance, with no columns or rows.

Instance Method Summary

• #<<(row : Array(Type))

  Append.

• #<<(row : Row)

  Append.

• #==(other : Dataframe) : Bool
• #[](header : String) : Dataframe::Column
• #[]=(header : String, new_column : Column) : self
• #add_column(header : String, type : ColumnType = String)

  Adds a new empty column to self.

• #add_column(header : String, data : Array(Type))

  Adds a new column to self, with content specified by data.

• #add_row(row : Array(Type))

  Append a new row to the bottom of self.

• #add_row(row : Row)

  Append a new row to the bottom of self.

• #columns : Hash(String, Column(String) | Column(Int32) | Column(Float64) | Column(Bool))

  Returns the columns of self as a Hash with the headers as keys, and Columns as values.

• #data : Array(Array(Bool | Float64 | Int32 | String | Nil))
• #each(& : Array(Type) -> ) : Nil

  Iterates over the rows of self.

• #each_row(& : Row -> ) : Nil

  Iterates over the rows of self, returning each row as an instance of Row.

• #full_join(other : Dataframe, on : Array(String)) : Dataframe

  Returns a new Dataframe that is the result of a full join of the receiver and other, using the headers in on to match rows.

• #headers : Array(String)

  Returns the column names as an Array.

• #inner_join(other : Dataframe, on : Array(String)) : Dataframe

  Returns a new Dataframe that is the result of an inner join of the receiver and other, using the headers in on to match rows.

• #left_join(other : Dataframe, on : Array(String)) : Dataframe

  Returns a new Dataframe that is the result of a left outer join of the receiver and other, using the headers in on to match rows.

• #order_columns(new_headers : Array(String)) : Dataframe

  Returns a new Dataframe with columns ordered by new_headers.

• #order_columns!(new_headers : Array(String)) : self

  Modifies self by rearranging columns in order specified by new_headers.

• #reject(& : Row -> ) : Dataframe

  Returns a Dataframe with all the elements in the collection for which the passed block is falsey.

• #reject!(& : Row -> ) : self

  Modifies self, deleting the rows in the collection for which the passed block is truthy.

• #reject_columns(headers : Array(String)) : Dataframe

  Returns a new Dataframe without the given columns.

• #reject_columns!(headers : Array(String)) : self

  Removes a list of columns.

• #rename_column(old_header, new_header)

  Changes the header of the specified column to a new value.

• #right_join(other : Dataframe, on : Array(String)) : Dataframe

  Returns a new Dataframe that is the result of a right outer join of the receiver and other, using the headers in on to match rows.

• #row_count

  Returns the number of rows in the Dataframe.

• #rows : Array(Row)

  Returns the data of the Dataframe as an array of Row.

• #select(& : Row -> ) : Dataframe

  Returns a new Dataframe with only rows for which the passed block is truthy.

• #select!(& : Row -> ) : self

  Returns a new Dataframe with only rows for which the passed block is truthy.

• #select_columns(headers : Array(String)) : Dataframe

  Returns a new Dataframe with the given columns.

• #select_columns!(headers : Array(String)) : self

  Removes every column except the given ones.

• #shape : Tuple(Int32, Int32)

  Returns a Tuple of the dataframe's dimensions in the form of { rows, columns }

• #sort_by(& : Row -> ) : Dataframe
• #sort_by(column : String, desc = false) : Dataframe
• #sort_by!(& : Row -> ) : self
• #sort_by!(column : String, desc = false) : self
• #to_csv(separator : Char = CSV::DEFAULT_SEPARATOR, quote_char : Char = CSV::DEFAULT_QUOTE_CHAR) : String

Constructor Detail

Instance Method Detail

column = dataframe.columns["Age"].as(Dataframe::Column(Int32))

column.map! do |e|
  e.nil? ? e : e + 1
end