The duplicates report output shows the number of replicate rows over all variables.
Jbl tws 4 manualĬlearly, the output from duplicates report and duplicates report id differ. The duplicates examples command lists one example of each duplicated set. We could have used the duplicates examples command instead of the duplicates report command. This is followed by duplicate reports idwhich gives the number of replicate rows by the variables specified in this instance we have just id. We start by running the duplicates report command to see the number of duplicate rows in the dataset. This leads to unique and 5 duplicated observations in the dataset. In the dataset, the variable id is the unique case identifier. The rationale for changing a value is to mimic what may happen in practice we often search for "duplicate" cases that are not identically entered into the dataset. Also, to evaluate the sensitivity of the command, we change a value of one of the duplicate observations. Therefore, we add five duplicate observations to the data, and then use the duplicates command to detect which observations are repeated. This example uses the High School and Beyond dataset, which has no duplicate observations. This user-written command is nice because it creates a variable that captures all the information needed to replicate any deleted observations. The second example will use a user-written program. The first example will use commands available in base Stata. There are two methods available for this task.
Stata drop duplicates how to#
These merges make sense when you have hierarchical data, and one data set contains information about the level one units while the other contains information about the level two units.This Stata FAQ shows how to check if a dataset has duplicate observations. In a one-to-many or many-to-one merge, one observation from one data set is combined with many observations from the other the difference between one-to-many and many-to-one being whether the master data set has the "many" or the using data set. For example, you might merge the answers people gave in wave one of a survey with the answers the same people gave in wave two of the survey. A one-to-one merge makes sense when the observations in both data sets describe the same things, but have different information about them. In a one-to-one merge, one observation from the master data set is combined with one observation from the using data set. Reshaping data in Stata (wide to long and long to wide) There are, in theory, four kinds of merges. Stata calls it merging when observations from the two data sets are combined. If a variable only appears in one data set, observations from the other data set will be given missing values for that variable. The data sets should have the same or mostly the same variables, with the same names. For example, you might append a data set of people from Wisconsin to a data set of people from Illinois. Appending makes sense when the observations in both data sets represent the same kind of thing, but not the same things. Stata calls it appending when you add the observations from the using data set to the master data set. Stata always works with one data set at a time, so you will always be combining the data set in memory the master data set with another data set on disk called the using data set, for reasons that will be clear when you see the syntax. Stata tries to make sure you've thought through what you're doing, but can't tell you what makes sense and what doesn't. Otherwise you can end up with a data set that you think is ready for analysis, but is really utter nonsense. Adesione al nuovo sistema di pagamenti pagopa – scadenza del Before combining data sets be sure you understand the structure of both data sets and the logic of the way you're combining them. However, it's also very easy to get wrong. Combining two data sets is a common data management task, and one that's very easy to carry out. If you're new to Stata we highly recommend reading the articles in order. For a list of topics covered by this series, see the Introduction. This is part eight of the Stata for Researchers series.