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Many varieties of ASCII tables can be handled, but the simplest (and default) is the comma-separated value (CSV) style as shown in the example below:
h1,h2,h3,h434,23,54,Saturn76,34,65,10,Mars55,44,22,19,Jupiter
Each column contains a field and each row contains a record. The (optional) first row contains the name of each column. The remainder of the rows contain comma-separated values (other separator options are possible). The Table Reader icon allows the user to specify how their table is formatted, which columns to read and which data types are in each column. If no data types are specified, then the first row of data will be examined and an attempt made to identify the data type (number or string) of each column.
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The following example shows a table file with 4 rows of meta-data, followed by a header row, followed by combined-space-delimited data rows:
type=FLEXTRA
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cfl=2.00
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cflt=2.00
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date=20111114
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dx=1.00
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dy=1.00east=30.00
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west=-10.00
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integration=PETTERSSEN
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interpolation=LINEARmax_w_int=21600SECONDS
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model_comment=FLEXTRA
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north=75.00
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south=30.00
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time=90000
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tr_type=3-DIMENSIONAL
...
...
SECS
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LONGIT
...
LATIT
...
ETA
...
PRESS
...
Z
...
Z-ORO
...
PV
...
THETA
...
0
...
-0.8300
...
51.5700
...
0.9518
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963.5
...
500.0
...
405.7
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1.450
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282.8
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3600
...
-1.1573
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51.6643
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0.9532
...
964.1
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491.8
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393.7
...
1.095
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282.7
...
7200
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-1.4730
...
51.7426
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0.9540
...
964.0
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489.7
...
387.3
...
0.781
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282.710800
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-1.7778
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51.8056
...
0.9541
...
963.3
...
493.5
...
386.1
...
0.509
...
282.814400
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-2.0913
...
51.8501
...
0.9548
...
961.8
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502.9
...
380.4
...
0.468
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282.918000
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-2.4282
...
51.8955
...
0.9564
...
960.3
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511.7
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366.1
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0.499
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283.121600
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-2.7885
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51.9420
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0.9590
...
959.0
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519.3
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343.5
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0.596
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283.3
The next section shows some Macro code to parse this table.
When delimiters are not combined, missing values are easily identified as the following three example rows show:
6,,8,7,86,7,
When delimiters are combined, it is no longer possible to identify missing values. In the Macro language, the bitmap() function can be used to convert values to missing values.
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After being read with the read_table() function, a table's columns can be accessed either by index or by name. A column will either be a vector of numbers or a list of strings. Meta-data can also be queried. The following example code illustrates how to handle table data in Macro:
my_table
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=
...
read_table(
...
table_delimiter
...
:
...
"
...
",
...
table_combine_delimiters
...
:
...
"on",
...
table_header_row
...
:
...
0,
...
table_data_row_offset
...
:
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3,
...
table_filename
...
:
...
"table_with_metadata.txt",
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table_meta_data_rows
...
:
...
1)for
...
i
...
=
...
1
...
to
...
count(my_table)
...
do
...
#
...
print
...
each
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column
...
print(name(my_table,
...
i),
...
'
...
:
...
',
...
values(my_table,
...
i))end
...
forkeys
...
=
...
metadata_keys(my_table)print(keys)print(metadata_value(my_table,
...
keys))
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#
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print
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all
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keys/valuesprint(metadata_value(my_table,
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'type'))