Use list to list data when you are doing so.
Stata drop duplicates how to#
Can you help me how to do this? I am relatively new to Stata. For instance, if I have the same observation four times, I want to drop three of them. However, some of these observations are duplicate. Matthias Enichlmayr.ĭrop duplicate observations 29 Jun Hi, I have a data set in Stata and I have a variable, with almost a million observations. Stata shows missing values as dots if you view a dataset with the browse command.Login or Register Log in with. Deleting missing values is, however not always straightforward.
The Stata result screen will show the result of this action: number of observations deleted. Deleting observations can be done using the missing value command: drop if mi variable.įor example: drop if mi Totaldebt. A range of variables next to each other can also be dropped with a single command. In this case it may be a good idea to delete them as they serve no purpose here. Filed under: CompustatData managementStataWharton. Some variables will then be changed to save space. When you work with much data over a long time it is also a good idea to save space and memory by compressing the database with the command: compress. To keep track of your versions of the database you can fut a date in the name of each version. You can also experiment a bit with a copy and you should definitely save the actions that you choose the finalize in a Do -file and when yiou continue from there again start with a copy. When you are performing such cleaning actions as described above it is a good idea to first make a copy of your database before you do all this and save the actions as there is no undo like in many programs. Another version of removing duplicates may have to do with the number of necessary observations by entity in a dataset. This command checks the whole dataset with all variables for all observations for duplicates and stores the result as a number in the new variable with the name newvariable. The command to tag the duplicates is: duplicates tag, gen newvariable. If you are working with a large dataset it may be a good idea to first tag possible duplicates and then have a look before removing these. Personally I think removing duplicates without first checking may not always be the smart thing to do. For instance: duplicates drop CIK yearforce.
Stata drop duplicates code#
I usually combine a unique ID code with a specific event year or date. The Stata command to remove duplicates should be chosen carefully. In Compustat you run the risk of duplicates if, for instance, you only need data for industrial type companies but, when doing the search in the Fundamentals Annual database you forget to unmark the option FS at the screening options at Step 2 in WRDS. Using data from some specific databases may also get you unintentional duplicate data. Another instance is: when you have received the dataset from a researcher or organization and need to remove superfluous data that may not be relevant to your own research. Related Book R For Dummies.When you work with large datasets or big data it may happen that after working with it for some time you need to take a good look at what has happened to the data. With over 20 years of experience, he provides consulting and training services in the use of R. So, to remove the duplicates from irisyou do the following. Remember that there are two ways to exclude data using subsetting. Now, to remove the duplicate from irisyou need to exclude this row from your data. You also can tell this by using the which function. If you look carefully, you notice that row is a duplicate because the rd element of your result has the value TRUE. So, for example, with the data frame iris. If you try this on a data frame, R automatically checks the observations meaning, it treats every row as a value. This means that for duplicated values, duplicated returns FALSE for the first occurrence and TRUE for every following occurrence of that value, as in the following example. R has a useful function, duplicatedthat finds duplicate values and returns a logical vector that tells you whether the specific value is a duplicate of a previous value. A very useful application of subsetting data is to find and remove duplicate values.
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