What's New in GAUSS 21

GAUSS 21 introduces a new and fast datamangement. The new dataframes and interactive data management make work more enjoyable and save hours of time.

Easy and Fast Data Management in GAUSS 21

New GAUSS dataframes make data easy to read and make code and results clearer

Close-Up of new Dataframes

Clearer Code and Results with Dataframes

Customize your date display

Reference your data by name

See your data your way with GAUSS dataframes

• Missing value support.
• Categorical, date, string, and numeric data.
• Reference by name or traditional matrix indexing.
• Programmatic and interactive support:
  • Category base case, labels and order.
  • Date display format.
• Simpler data cleaning.
• Clear data view and reporting.
• Compatible with matrices and older code and application modules.

Easy and fast interactive data management

Interactive data import

• One-click import and preview.
• CSV, Excel, SAS, Stata, SPSS files.
• Automatic code generation.
• Specify values to import as missing.
• Select and rename variables.
• Live preview.
• Manage categories.

View, rename, and reorder categorical variables

Intuitive interactive controls to:

• Set the base case.
• Rename labels.
• Set category order.

Import dates in any format

Non-standard date formats are no problem.

• Auto-detects 30 formats.
• Specify any custom format.
• Any characters.
• Any order.

Interactive data filter

• Simple dropdown options.
• Create multiple filters.
• Automatic code generation.
• Available for data before and after loading.
• Handles missing data.
• Live preview.
• Intuitive date filtering.

Complete List of New Features

1. GAUSS 21 now supports dataframes with date, categorical, string and numeric columns.
2. loadd() now returns a dataframe. This is a behavior change that can be reverted by the #defines in policy.dec.
3. loadd() now accepts an optional input with support for additional data loading options, such as selecting a row range, specifying Excel sheets, CSV delimiters, the header row, values to interpret as missing values, and the quote character.
4. loadFileControlCreate() fills a loadFileControl structure with the defaults for the new data loading options.
5. Formula string keyword cat now supports an optional input to set the base case.
6. Formula string keyword date now supports an optional input to specify the incoming date format.
7. Logical operators (.<, .>, .<=, .>=, .==, .!=) support comparisons with date strings and categorical variable labels.
8. glm() and olsmt() support dataframes and automatically turn categorical variables in to dummy variables.
9. dstatmt() supports dataframes and counts missing values by default.
10. saved() will write, string, categorical and date variables. The variable names argument is now optional.
11. New functions setcolnames() and getcolnames() set and return columns names of a matrix, or dataframe.
12. New functions setcoltypes() and getcoltypes() set and return the variable types of the columns of a matrix, or dataframe.
13. New function setcolmetadata() sets column names and variable types for a matrix or dataframe.
14. New function recodecatlabels() changes the labels displayed for a categorical variable in a dataframe.
15. New function reordercatlabels() changes the order of the labels displayed for a categorical variable in a dataframe.
16. New function setbasecat() sets the base category of a categorical variable.
17. New functions setcollabels() and getcollabels() set and return the integer key values and string labels of categorical variables in a dataframe.
18. New function getcollabelvalues() returns the string labels for every observation of a categorical variable as a string array.
19. New function setcoldateformats() sets the display format of a date variable, getcoldateformats() returns the display format.
20. New function hasmetadata() returns a 1 if the input is a dataframe.
21. New function asmatrix() turns a dataframe into the equivalent matrix.
22. New function order() reorders columns of a dataframe by name.
23. New function frequency() computes a frequency table for a categorical variable.
24. The Data Import Window now supports variable selection, interactive filtering and automatic code generation.
25. The suffix for duplicate headers in the import dialog now start at _2 instead of _1.
26. Symbol Editors support the same variable selection and filtering options added to the Data Import Window.
27. Formatting in the Symbol Editor is now on a per column basis.
28. Character vectors now show up to 8 characters in the Symbol Editor (the length is NOT limited for string arrays or dataframe string and category columns).
29. CSV sniffing in the Data Import Window will now only occur for the first 200 rows instead of the entire file to improve performance.
30. The Project Folders window now automatically shows contents of the Current Working Directory.
31. The Project Folders window now shows new files without need to refresh.
32. The default setting for the run button is now to run the active file. This can be changed in Preferences to be the same as previous versions.
33. Find Usages for local variables now reports only instances of the local variable.
34. CTRL+F1 will now find the declaration of local variables in a procedure.
35. New Preference option to specify the default directory for File > Open.
36. Assignments to arrays of structures in threadFor loops is now allowed.
37. Bug fix: Memory leak in lagtrim().
38. Bug fix: Memory leak in specific situation with EuropeanBSCall().
39. Bug fix: threadFor would not allow certain cases with multiple references to a slice variable to compile.
40. Control Var node on Data Page is now collapsed by default.
41. New example files for dataframe 'get' and 'set' functions as well as frequency() and plotFreq().
42. GLM example files updated to use dataframes.