xlsReadM#

Purpose#

Reads from an Excel® spreadsheet into a GAUSS matrix.

Format#

mat = xlsReadM(file[, range[, sheet[, vls]]])#

Parameters:

file (string) – name of .xls or .xlsx file.
range (string) – Optional input, range to read, e.g. “A2:B20”, or the starting point of the read, e.g. “A2”. Default = “A1.
sheet (scalar) – Optional input, sheet number to read from. Default = 1.
vls (null string or 9x1 matrix) – Optional input, specifies the conversion of Excel® empty cells and special types into GAUSS (see Remarks). A null string results in all empty cells and special types being converted to GAUSS missing values.

Returns:

mat (matrix) – or a scalar error code.

Portability#

Windows, Linux and macOS

The vls input is currently ignored on macOS and Linux. Missing values will be returned for all cells that are empty or contain errors.

Examples#

Basic Example#

// Create file name with full path
file = getGAUSSHome("examples/tbill_3mo.xlsx");

// Read in all data below header line
x = xlsReadM(file, "A2");

After the code above, the first 10 rows of x should be equal to:

19820101000000    12.92
19820201000000    14.28
19820301000000    13.31
19820401000000    13.34
19820501000000    12.71
19820601000000    13.08
19820701000000    11.86
19820801000000        9
19820901000000     8.19
19821001000000     7.97

Read From a Range#

// Create file name with full path
file = getGAUSSHome("examples/yarn.xlsx");

// Read in data from rows 2-9 of column 'D'
x = xlsReadM(file, "D2:D9");

After the code above, x should be equal to:

Reading dates#

// Create file name with full path
file = getGAUSSHome("examples/tbill_3mo.xlsx");

// Read the first element below the header from the first column
date_1 = xlsReadM(file, "A2:A2");

If the Excel file has marked a cell as a date, GAUSS will read it in DT scalar format. After the code above, date_1 will be equal to:

19820101000000

Dates in DT scalar format can be passed in directly to plotTS() to create time series plots, and also handled by other GAUSS date handling functions. For example, we can convert date_1 to a string with the function dttostr() (date to string) like this:

date_str = dttostr(date_1, "MO-DD-YYYY");

After which, date_str will be equal to:

"01-01-1982"

Specify Sheet Number#

// Create file name with full path
file = getGAUSSHome("examples/nba_ht_wt.xls");

// Pass in '1' as the third input, to specify the first sheet
x = xlsReadM(file, "C2:C5", 1);

After the above code, x will equal:

Remarks#

If range is a null string, then by default the read will begin at cell “A1”.
Use loadd() to load all rows, except for the header row, from specific columns of an Excel file.

If xlsReadM() fails, it will either terminate and print an error message or return a scalar error code, which can be decoded with scalerr(), depending on the state of the trap flag.

`trap 0`	Print error message and terminate program.
`trap 1`	Return scalar error code.

2.1 An error message example

// Will end the program and print an error message
x = xlsReadM("nonexistent_file.xlsx");

2.2 Turn off error message

// Turn error trapping on
trap 1;
x = xlsReadM("nonexistent_file.xlsx");

// Check to see if 'x' is a scalar error code
if scalmiss(x);
   // Code to handle error case here
   print "Excel file not found";
endif;

// Turn error trapping off
trap 0;

By default, empty cells are imported as GAUSS missing values. The vls argument lets users control the import of Excel® empty cells and special types, according to the following table:

Row Number

Excel® Cell

1

empty cell

2

#N/A

3

#VALUE!

4

#DIV/0!

5

#NAME?

6

#REF!

7

#NUM!

8

#NULL!

9

#ERR

Use the following to convert all occurrences of #DIV/0! to +Infinity, and all other empty cells and special types to GAUSS missing values:
```
// Create a 9x1 vector of missing values
vls = reshape(miss(0, 0), 9, 1);

// Set the 4th element of 'vls' to +Infinity so that
// Excel #DIV/0! cells will be imported as +Infinity
vls[4] = __INFP;

x = xlsReadM("myfile.xlsx", "A1", 1, vls);
```

Row Number	Excel® Cell
1	empty cell
2	`#N/A`
3	`#VALUE!`
4	`#DIV/0!`
5	`#NAME?`
6	`#REF!`
7	`#NUM!`
8	`#NULL!`
9	`#ERR`