How to get data into DataLab

One of the major practical obstacles to use any program for data interpretation is the way how to import external data. In order to make easy and efficient use of a program, the data should be imported easily from a number of commonly available data formats. DataLab therefore offers several ways to import data into the data matrix:

Load data from a proprietary DataLab format: this is the most convenient way to load data since not only the data are loaded but also the set-up of the windows and the system parameters (see Loading IDT Files). Of course this data format can only be used if the data have been previously saved using this format.

Import from a simply formatted text file: DataLab uses a simple text-based data format (ASC format) in order to input external data. ASC files may be loaded either directly or by using the Windows clipboard.

Import of Microsoft Excel files: DataLab supports the importing of single worksheets of Excel files.

Import of CSV files: DataLab is able to load "comma separated values" (CSV) files. (Remark: to our experience CSV files should be avoided as this format is by no way standardized and suffers from a plethora of different versions).

Importing simple text files: If you have a retangular array of text data you can use the Import Simple Text tool to load this kind of dataset (either from a file or from the Windows clipboard).

Importing complex text files: Text data exhibiting a complex structure be imported by using either the Import Complex Text Data tool or by writing a script using DLabPascal.

Copying data from the Windows clipboard. This is a convenient way to bring data into the numeric editor, although it is only useful for simply structured data as any additional data is lost (only the bare numbers are taken).

Enter the data manually using the built-in numeric data editor.

Generating artificial data. In addition to these methods of importing external data, DataLab offers the possibility of generating artificial data. This may sound strange, but in many circumstances (simulations, experimental design, random test data, etc.) artificial data would be of great help. Therefore DataLab provides several tools to create artificial data:

• A easy to use 2D Data Designer enables you to create two-dimenional datasets by drawing the data points in a two-dimensional chart.
• A simple mathematical formula interpreter which allows us to create data "quick and dirty".
• A versatile random number generator provides a means of creating random numbers of almost arbitrary distributions.
• Finally DataLab is fully programmable using the built-in object oriented script language DLabPascal. This is the most flexible way to create virtually any data you can think of and provides you with the power of a high-level programming language to automate your data analysis tasks.