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databank.toCSV (+databank)

Write databank to CSV file

Syntax

fieldsSaved = databank.toCSV(inputDb, fileName, dates, ...)

Input Arguments

inputDatabank [ struct | Dictionary ]

Input databank whose time series and numeric entries will be serialized to a character vector.

fileName [ string ]

Name of a CSV file to which the databank will be saved.

dates [ Dater | Inf ]

Dates or date range on which the time series will be saved; Inf means a date range from the earliest date found in the inputDatabank to the latest date.

Output Arguments

fieldsSaved [ string ]

List of databank fields that have been written to the output file fileName.

Options

NamesHeader="Variables->" [ string ]

String that will be put in the top-left corncer (cell A1).

Class=true [ true | false ]

Include a row with class and size specifications.

Comments=true [ true | false ]

Include a row with comments for time series.

Decimals=[ ] [ numeric ]

Number of decimals up to which the data will be saved; if empty the numeric format is taken from the option Format.

Format="%.8e" [ string ]

Numeric format that will be used to represent the data, see sprintf for details on formatting, The format must start with a "%", and must not include identifiers specifying order of processing, i.e. the "$" signs, or left-justify flags, the "-" signs.

FreqLetters=["Y", "H", "Q", "M", "W"] [ string ]

Vector of five letters to represent the five possible date frequencies except daily and integer (annual, semi-annual, quarterly, monthly, weekly).

MatchFreq=false [ true | false ]

Save only those time series whose date frequencies match the input vector of dates.

NaN="NaN" [ string ]

String to represent NaN values.

TargetNames=[] [ empty | function ]

Function transforming the databank field names to the names under which the data are saved in the CSV file; TargetNames=[] means no transformation.

UserDataFields=[] [ empty | string ]

List of user data fields that will be extracted from each time series object, and saved to the CSV file; the name of the row where each user data field is saved is .xxx where xxx is the name of the user data field.

Description

Example

Create a simple database with two time series.

D = struct( );
D.x = Series(qq(2010, 1):qq(2010, 4), @rand);
D.y = Series(qq(2010, 1):qq(2010, 4), @rand);

Add your own description of the database, e.g.

D.UserData = {'My database', datestr(now( ))};

Save the database as CSV using databank.toCSV, 

databank.toCSV(D, 'mydatabase.csv');

When you later load the database, 

D = databank.fromCSV('mydatabase.csv')

D =

   UserData: {'My database'  '23-Sep-2011 14:10:17'}
          x: [4x1 Series]
          y: [4x1 Series]

the database will preserve the 'UserData'' field.

Example

D = struct( );
D.x = Series(qq(2010, 1):qq(2010, 4), @rand);
D.y = Series(qq(2010, 1):qq(2010, 4), @rand);
databank.toCSV(D, 'datafile.csv', Inf)