Stata/Data Management

Read and import data Usually, data are loaded into memory using the use command. The clear option makes it sure that the current database in memory will be removed without saving the last changes. use "W:\Data\…\table.dta" , clear The cd command allows to specify a working directory and makes it easier to load tables into memory. cd "W:\Data\" use table, clear Stata9 users can import Stata10 datasets using the use10 command. use10 table, clear Some example datasets are stored in the Stata directory. They can be loaded into memory using the sysuse command. . sysuse cancer, clear . sysuse smoking, clear . sysuse auto, clear . sysuse jspmix, clear You can import a Comma Separated Value (CSV) format using insheet insheet using "W:\Data\…\table.csv", delim(";") See also 'webuse' for internet data 'xmluse' for xml files 'infile' for text files 'input' for entering data from keyboard 'infix' 'fdause' for SAS xport data If none of these command works, you may use Stat/Transfer FTRANS: module to batch convert file formats Save and export data save save table, replace If you use Stata10 you can export to Stata9 format using saveold saveold table, replace outsheet : export to tab delimited or csv format. outsheet using "W:\Data\…\table.csv", replace comma See also outfile xmlsave fdasave Append and merge The standard Stata command is merge. However, the user-written command mmerge is safer and gives a better output. This command may be installed using ssc install mmerge command or using findit mmerge. dmerge joinby merge all possible pairs between the datasets append if you have two datasets with the same variable but different observations, you can make one dataset using the append command. use data_1, clear append data_2 br Describe a datasets des des, s codebook codebook2 Detect missing values tabmiss npresent nmissing You can convert missing values to values using the mvencode command. mvencode exg ga dvg verts eco dr dvd fn reg mnr div, mv(0) override Variables Very often you have to convert variable from a string to a numerical format. There are several way to do it. If you already have numeric values in your string variable, you should use destring. Otherwise you should use the encode command. Encode will automatically create a numerical variable and will use as a value label the string values of the previous variable. gen egen replace recode drop keep rename 'vallist' gives the list of all categories of a categorical variable in Stata. vallist codep Dealing with labels lab var lab list lab define lab value Expand You can expand a dataset (ie multiplying observations by a given factor) using the expand command. This is useful for generating panel data models. In the first example, we draw 10 observations in a standard normal distribution and we replicate each observation once. clear set obs 10 gen u = invnorm(uniform()) expand 2 sort u br It is also possible to pass an integer variable as an argument to expand. clear set obs 10 gen u = uniform() gen var = 1 + int(10 * uniform()) expand var sort u br clear set obs 10 gen u = invnorm(uniform()) expandcl 2 , gen(cl) Data Storage types All numeric types in Stata are normal "signed" quantities except that the highest 27 values are reserved for the "missing" types (., .a, .b, ..., .z). The storage size of the each variable is as follows: Variable Size (in bytes) byte 1 int 2 long 4 float 4 double 8 string 1 per-letter (therefore only ASCII characters, not full Unicode/UTF-8) Random Number Generation Graphics