ParseCSV

new to Analytica 5.0

Converts a text value read in from a file with CSV (Comma-Separated Values) format into a 2D array. By default, it converts values that appear to be numbers and dates into Analytica numbers and dates. It offers lots of optional parameters to control the column and row indexes, and handle the many variants of the CSV format -- for example, with nonstandard characters that separate columns, rows, and for the quotes around text.

ParseCSV( csvText, columnIndex, rowIndex, separator, firstLineIsHeader, trimCells, columnsToKeep, rowIndexLabelColumn, parseFlags, dateTemplate, decimal, quote )

Normally, you use this with ReadTextFile() to read in the file:

ParseCSV(ReadTextFile( filename ))

Given text in CSV-format (Comma Separated Values), it returns a two-dimensional array containing the data. By default, it assumes the same CSV format conventions as Excel -- that is, commas to separate columns, newline to separate rows, and double quotes to enclose elements that may contain commas or newlines. By default, it returns the array with local indexes, .Column and .Row.

Indexes for result

If you have an existing column or row index you want to use instead of the default local indexes .Column and .Row, you can specify one or both as optional parameters «columnIndex» and «rowIndex». If «columnIndex» (or «rowIndex») is shorter than the number of columns (or rows) in the original, it ignores the extra columns or rows. If the given index is is longer than expected, it pads the result with NULL for the extra columns (or rows.)

Non-comma separator

By default, it assumes that cells (columns) are separated by commas (,), as you would expect in a "comma-separated" format! You can specify any character (or a text with multiple characters) to the optional parameters «separator». Common separators include '|', Chr(9) (tab), ';'

Spaces around values

By default it trims away any leading or trailing spaces around each value. Set «trimCells» to False if you want to retain those spaces. It never trims spaces inside quotes.

Header column in data

By default, it assumes that the first row contains columns names, which is common in CSV file, and it puts those names into the local .Column index, unless you specify «columnIndex». In that case, the first row does not appear in the data. It also assumes the first row contains column names if you specify «columnsToKeep» or «rowIndexLabelsColumn». You can override this default behavior by setting «firstLineIsHeader» to false, in which case it treats the first row as data. Conversely, you can override the default of treating the first line as data when you specify a «columnIndex» by setting «firstLineIsHeader» to true.

Subset of or re-ordered columns

The «columnsToKeep» parameter lets you select a subset of the columns, or re-order them.

To extract just a single column, you can specify either the name (from the first line) or the number of the column that you want to keep to «columnsToKeep». You can omit «columnIndex».

To extract several columns or to reorder columns, you should specify a «columnIndex». If the column index contains the column names from the CSV (in any order), you can specify it also to «columnsToKeep» e.g., ParseCSV(csv, col, columnsToKeep:col). Or you can pass «columnsToKeep» a 1D array of names or numbers indexed by «columnIndex». .

If you pass a list or array to «columnsToKeep», but don't specify «columnIndex», it will still extract the specified columns, but less efficiently because array abstraction repeats the call for each element in the array passed to «columnsToKeep», and it parses the «csvText» anew each time.

Using a column for row labels

You can use «rowIndexLabelsColumn» to specify a column number to use for the labels for the local row index. It then removes that column from the array (unless you specify «columnIndex» with «matchColumnLabels» and explicitly include that column). For example, ParseCSV(csvText, rowIndexLabelsColumn: 1) treats the first column as row index labels rather than as array cells.

Parse flags

«parseFlags» is a bit-field of flags to control whether it should try to convert cells into a number or date. The default (0) corresponds to the standard Excel conventions -- i.e. it converts an unquoted number or a number between quotes into a number. You can add flags together to combine their effects:

0 = Parse both quoted ("52") and unquoted (52) cells.
1 = Don't parse any cells. E.g., return ="52", "52" and 52 as text.
2 = Don't parse quoted cells. E.g., "52" is text, but 52 is numeric.
4 = Disable the '=' prefix (="0042" normally suppressed parsing).
8 = Recognize backslash-escaped quotes inside quotes (in addition to the doubling of quotes, which is the usual CSV standard).
16 = Disable generalized date parsing. When on, only the format 6-May-2016 is recognized as a date but not other formats. This flag dramatically speeds up parsing times for data with no other date formats.

Date Formats

Use the «dateTemplate» parameter to specify the international ordering that should be used for parsing dates. Use the letters "d", "M" and "y" to specify the ordering of these components. For example, with a «dateTemplate» of "d/M/y", the text "11/10/9" parses as 11-Oct-2009, whereas with a «dateTemplate» of "y/M/d" it would be 9-Oct-2011, and with "M/d/y" it would be 10-Nov-2009.

This parameter uses the same conventions used in the Custom date formats template in the Number Format Dialog, but only the relative ordering of the day, month and year patterns matter. Hence, all these work equivalently: "dMy", "dd/MM/yyyy", "d-M-yy", "d M yyyy". Also, upper/lower case matters! "M" must be capital (because "m" means minutes").

Decimal point and thousands separators

By default, it assumes that '.' (dot or period) separates the whole number from the fractional part of a decimal number -- i.e. the convention used in English-speaking countries. You can tell it to use ',' (comma) by setting the «decimal» parameter. That parameter accepts only '.' (dot) or ',' (comma).

When comma is used for «decimal», the «separator» is usually something other than comma -- commonly semi-colon ';'. If the «decimal» and «separator» are both commas, there must be quotes around any numbers containing decimals.

When «decimal» is dot, you can use commas to group digits, such as "525,948.77". Conversely, when «decimal» is comma, you can use dot to group digits, such as "525.948,77" (for five hundred twenty-five thousand, nine hundred eight and 77 hundredths).

Quote character

The quote character is used in CSV to enclose numbers or text that may contain separators. By default, the quote character is double quote ("). You can specify a different quote character using the «quote» parameter. The most common other quote character used is the single quote ('). To type a single quote in Analytica, you can type doubleQuote SingleQuote doubleQuote ("'"). Analytica lets you use either matching single quotes or matching double quotes to enclose text strings.

The CSV format

There is no single well-defined CSV standard. Undocumented conventions used by Excel are often seen as the most definitive "specification". The article at Comma Separated Values (CSV) Standard File Format is relatively easy to read and covers the basics well, without being the most comprehensive reference.

Each "record" (or row) is a CSV file is delineated by a newline, either CR, LF or CRLF. Each value within a row is separated from the next field by a separator character, usually comma (hence the name "Comma-separated values"), although other characters or character sequences are also sometimes used, including commonly TAB (Chr(9)), bar ('|'), semi-colon (';') and even space.

A row of data might look like this:

California, CA, "39,144,818", 163696, Sacramento, "Edmund Gerald ""Jerry"" Brown, Jr.", ="95814", 9/9/1850

Both textual and numeric values may or may not be surrounded by quotes. Any value containing the separator character or a newline must be surrounded by quotes. Quotes are always the double-quote character ("). A value may also be a date (e.g., 9/9/1850). Spaces to the left or right of a value are normally trimmed (unless you set «textTrim» to false).

When a value is read, if it parses as a valid date, it will be parsed as a date, otherwise if it parses as a valid number, it will parse as a number, and otherwise it will be read as text. The «parseFlags» parameter can be used to alter this behavior somewhat. To force a value to be read as text, even when it would be a valid number, use the equal-quote form, ="95814".

Note that new lines can appear within quoted values, so simply splitting CSV data on newlines does not reliably separate the data into rows.

The first line of a CSV file often consists of columns names, with data starting on the second row. But this is not always the case, some CSV files have no column headers with data starting on the first line.

Examples

The simplest usage is:

ParseCSV( csvText )

which follows the most common format and Excel standards.

To read in a CSV file:

ParseCSV( ReadTextFile( filename ) )

History

This built-in function was introduced in Analytica 5.0. For earlier releases, the Flat-file library contains ReadCsvFile and ParseCsvText functions. The ParseCSV is a substantial improvement.