Manipulating variables within datasets. Once you've uploaded data to Crunch, you'll likely want to spend some time cleaning up the metadata associated with your dataset. Legacy statistical programs offer only limited support for variable metadata, both in type and quality.
https://cran.r-project.org/web/packages/crunch/vignettes/variables.html
After you read your data into Stata it is important to prepare some documentation. In this section we will see how to create dataset, variable, and value labels, and how to create notes for the data or variables.
http://data.princeton.edu/stata/DataManagement.html
You can make them manually using the. %LET statement, or you can make the process automatic using the CALL SYMPUT in the DATA step or the INTO. statement in PROC SQL. To create a large number of different macro variables with different content, SAS software. also offers us the power of the CALL SET statement.
http://www2.sas.com/proceedings/forum2007/050-2007.pdf
Stata datasets are rectangular arrays with n observations on m variables. Unlike packages that read one observation at a time, Stata keeps all data in memory, which is one reason why it is so fast. There's a limit of 2,047 variables in Stata/IC, 32,767 in Stata/SE.
http://data.princeton.edu/stata/DataManagement.html
Stata 11 introduced a variables manager that allows editing variable names, labels, types, formats, and notes, as well as value labels, using an intuitive graphical user interface available under Data|Variables Manager in the menu system.
http://data.princeton.edu/stata/DataManagement.html
You can reference and extract variables from a dataset as if it were a data.frame, using the $, [, and [[ methods. track.var <- ds$track track.var ## track (categorical) ## ## Count ## Off on the wrong track 576 ## Generally headed in the right direction 285 ## Not sure 139.
https://cran.r-project.org/web/packages/crunch/vignettes/variables.html
In effect, it creates a macro variable for each variable in the data set. These macro variables have the same names as the. associated data set variables. At this point, these macro variables are empty.
http://www2.sas.com/proceedings/forum2007/050-2007.pdf
2. Data Management. In this section we describe Stata data files, discuss how to read raw data into Stata in free and fixed formats, how to create new variables, how to document a dataset labeling the variables and their values, and how to manage Stata system files.
http://data.princeton.edu/stata/DataManagement.html
The result is that the first value stored in the variable Name is now stored in. the macro variable &Name1; the second value is stored in the macro variable &Name2…etc. But there are even. more elegant ways to accomplish this task.
http://www2.sas.com/proceedings/forum2007/050-2007.pdf
If a large number of macro variables need to be created from data set variables, however, even these. solutions many require a great deal of typing. Furthermore, if the number of macro variables created for each data. set variable and observation is extremely large, the memory demands on the system can be huge. The SAS system. however, provides an elegant way to overcome these problems with the CALL SET routine.
http://www2.sas.com/proceedings/forum2007/050-2007.pdf
what are variables in a dataset
Macro variables are variables in a dataset. Macro variables are the variables in a dataset.