|Title||Dealing with very large datasets|
|Author||Kolver Hernandez, Boston College|
Use Stata/MP or Stata/SE. If you do not have Stata/MP or Stata/SE, please continue with this FAQ.
When the number of variables in a dataset to be analyzed with Stata is larger than 2,047 (likely with large surveys), the dataset is divided into several segments, each saved as a Stata dataset (.dta file). To work with information contained in two or more .dta files, it is necessary to merge the segments into a new single file that must not contain more than 2,047 variables. Here is a list of steps to construct a new database with information merged from different files. Any manipulation of the data made with a Stata do-file allows you to review and/or repeat the procedure more easily.
. use filename.dta
A unique ID for each case (observation) must be provided for each file to be merged. Typically, the ID for a time-series database is the date of the observation. For a cross-section database, it is the ID of the cross-section unit (family identifier, firm CUSIP, etc.), and in panel data, two characteristics are needed to identify each observation: date and ID. However, for panel data, sometimes a “case ID” is provided to facilitate merging.
You must ensure that the form in which the unique ID is held in each file must match; i.e., you cannot match a str8 (8-character string) to a str6 ID, nor can you match a string to an integer. Use Stata's describe command to ensure that the name and data type of the ID variable are the same in all files.
- If the useful variables can be listed more easily:
. keep caseID varname1 varname2 ... varnameN
- If the unwanted variables can be listed more easily:
. drop varname1 varname2 ... varnameN
Remember that the case ID must be part of the new file.
. sort caseID
. save newfile#.dta
- Read the master dataset (newfile1.dta recently created):
. use newfile1.dta, clear
- Merge the data with the using dataset (newfile2.dta):
. merge 1:1 caseID using newfile2.dta
- Tabulate _merge:
. tabulate _merge
The variable _merge is created automatically, and it takes the following values:
- _merge==1 if the observation was taken from the master data only
_merge==2 if the observation was taken from the using data only
_merge==3 if the observation match both master and using data
You can use the tabulated information to check if the data were merged as desired.
- Drop the _merge variable:
. drop _merge
- If there are more than two files to merge, use the current data in memory as the master dataset, and repeat steps 8b-8d for each file to be merged (newfile3.dta, newfile4.dta, .... newfileJ.dta).
. save newdataset.dta
Here is an example of how a do-file can be used to merge data contained in three hypothetical segments.
This do-file merges some variables from the .dta files: segment1.dta, segment2.dta, and segment3.dta into a new file named newdatabase.dta. This do-file will be documented in the log-file logmerge.smcl for further reference.
/* open the log file*/ log using logmerge.smcl, replace /*Generates three .dta files containing only desired variables*/ use segment1.dta, clear keep ID X11 X12 X13 sort ID save newfile1.dta, replace use segment2.dta, clear keep ID X21 X22 X23 sort ID save newfile2.dta, replace use segment2.dta, clear keep ID X31 X32 X33 sort ID save newfile3.dta, replace clear /*Merges the three new files generated*/ use newfile1.dta, clear merge 1:1 ID using newfile2.dta tab _merge /*check the file logmerge.smcl to verify that _merge takes the appropriate value*/ drop _merge /* if _merge is not dropped an error will be generated, up to this point two segments were merged successfully*/ merge 1:1 ID using newfile3.dta tab _merge /*check the file logmerge.smcl to verify that _merge takes the appropriate value*/ drop _merge /* the three segments were merged successfully, now save the final new > database*/ save newdatabase.dta clear log close /* The individual segment files may now be discarded or compressed if > desired */
Thanks to Petia Petrova for contributions to this document.