CSV files are plain-text files that have fields ending in the comma character and records ending in an end-of-line symbol or paragraph marker (linefeed/newline character, carriage return character, or carriage return-linefeed pair). Because text in fields may contain commas, commas within fields are enclosed in quotation marks: "," In additon, quotation marks within fields are changed to two quotation marks: ""
NOTE: iData can import CSV files that
were created by Apple Numbers or Microsoft Excel, but some other
applications may not follow that format exactly, in which case iData
may not be able to import their CVS files.
The CSV format is widely used to move data among database applications, each of which has its own native file format, but which can export and import files in this format.
Note: Due to the complexity of the CSV format,
we strongly suggest that you do not try to create CVS files by hand.
A common convention is that a CSV file can be exported with a new first record that contains the name of each field in that field. iData supports this convention. However, if you have a CSV file that does not contain field names in the first record, iData will use numbers for field names, and you can rename the fields later, using the Modify Fields command in the Fields sub-menu, under the Edit menu.
In addition to importing files in standard CSV format, it is also possible to import a text file containing lines of text (paragraphs, ending in single returns) using this function. If you select the Create new field-based datafile option, the result will be a new datafile with a single field, and with each line of text in that field in its own record. If desired, you can add more fields later, using the Modify Fields command in the Edit menu.
To import a CSV file:
1. In the Finder, make sure that the text file to be imported has a .csv, .txt or .text file name extension. This is the only way iData has of recognizing valid CSV text files. (Note: However, you should not try to import files of other types by simply changing the file name extension. This will not work, and may cause iData to crash.)
2. In iData, select CSV File... from the Import menu under the File menu.
3. In the Open dialog that comes up next, navigate to your CSV file, select it, and click the Open button.
4. The following dialog will appear. If there is no current datafile open that has the same number of fields as the file being imported, only the first option will be available.
5. If applicable, select one of the radio buttons. Here are what the options mean:
a. Create new field-based datafile - As you might expect, this will create a new datafile containing the imported CSV data. You will be able to save the new datafile with any name you desire.
b. Append to current datafile - If this option is available, it will cause newly imported records to be added at the end of the current datafile. If you are importing a later version of the CSV file that was used to create the current datafile, you will probably end up with duplicate records.
c. Merge into current datafile - If this option is available, after adding the newly imported records, iData will automatically remove all exact duplicates, so this is probably the best option for repeatedly updating a datafile for a particular CSV file. Note that removing duplicates requires that the datafile be sorted by the contents of all the fields in order, so if you have rearranged the datafile for any reason, that order will be lost.
6. If the incoming CSV file has field names in the first record, enable the Has field names in first record checkbox.
7. Click the OK button to start the import.
8. Once the import is complete, if you selected the first option, the result will be a new untitled datafile. In this case, we recommend that you save the new datafile right away, giving it the same name as the file from which it was imported, but retaining the required .id3 file name extension.
NOTE: There is no real "standard" for CSV file formats. As a result, different apps may produce slightly different files. We have tried to make iData as flexible as possible, but it is impossible to foresee all possibilities. If iData finds that a record has too many or too few fields (using the first record as the standard), you will see something like the following alert:
If you see this alert, you can use
iData's search function to find the errors and correct them manually if