![]() To return a dataset composed of summary statistics computed over multiple rows : Stataĭf %>% summarize(mean(v1, na.rm = TRUE), sd(v2, na.rm = TRUE)) The syntax for collapsing dataset is very similar to the syntax for modifying columns : just use summarize instead of mutate In case your dataset is very large, `mutate` one variable at a timer rather than using `mutate_at` ![]() When replacing every variable in the dataset, `dplyr` requires twice the amount of memory compared to data.table since a whole new dataset is temporarly created. To apply the same function to multiple columns, use across Stataĭf %>% mutate(across(c(v1, v2), as.character)) ![]() To modify only certain rows of a column: Stataĭf %>% mutate(v1 = ifelse(id = "id01", 0, v1)) This table gives the list of helper functions: Stata In dplyr, helper functions allow very similar results: Stata In Stata, wildcards allow to select multiple variables. This does not always require more memory: when subsetting columns, the new dataset is a shallow copy of the existing one - at least until the new dataset is modified. © W.Contrary to Stata, R returns a new dataset without destroying the existing one. Where XX will be replaced by the value Stata has computed, of course. This will store the values of the 2.5th and the 97.5 percentile in a matrix with two elements, and upon submitting the second command, Stata will anwer: This is a programmer's command, and hence the result must be requested from Stata with return list. Hint: If you need a percentile that is no integer, such as 2.5, you should try the _pctile command. that other content is available, such as the interquartile range ( iqr), minimum ( min) and maximum ( max), the sum ( sum) or, if there are weights, the unweighted sum ( rawsum), and finally the number of nonmissing observations ( count or n).that any number between 1 and 99 can be used to obtain the respective percentile,.that the option content may be abbreviated by c ,.Will display for the schools in your sample (row variable), separately for boys and girls (column variable), the number of cases ( freq), the mean math score, and the 10th, 50th and 90th percentile of the math score. Table school gender, content(freq mean math p10 math p50 math p90 math) It can be used to display up to five statistics per cell, with cells defined by the categories of one or two variables. Yet another way is to use the table command. More than two variables, however, are not permitted. Will display the income for each sex within each class. While there is a number of other possibilities to create an overview of means and S.D.s, an nice feater of tabulate is that it can display these statistics conditional on two variables combined. As to the standard deviation see my remark above. Will display the mean and the standard deviation of income, plus the number of observations, for each social class. Let's assume that variable "class" indicates the social class of the persons in your sample and "income" their income. For the time being, please refer to the User's Guide.Ī related, but somewhat different possibility is to display summary statistics for a variable contingent on the values of another variable. ![]() It offers more flexibility in the choice of statistics displayed. The help file will show you how to get the different measures.Ĭommand tabstat is yet another way to compute a number of sample statistics. Dirk Enzmann has written an ado file moments2 that allows you to pick the measure of your choice. The option "detail" (abbreviated as "d") will cause Stata to deliver, in addition to the mean and the S.D., several further statistics: Various percentiles, the four smallest and the four largest values, the variance and finally skewness and kurtosisĪctually, quite a number of measures have been proposed in the literature for skewness and kurtosis, and particularly concerning kurtosis the implementation in Stata's summarize is somewhat unfortunate. Several variables can be listed, as in the following expanded example: (In other words, when computing the variance, the denominator is not n, the number of cases in your dataset, but n-1.). The standard deviation is calculated on the assumption that your data are a sample from a population and therefore is an estimation for that population and not simply the standard deviation of the data at hand. Will display the number of observations for this variable, the arithmetic mean (commonly abbreviated as mean), the standard deviation and the minimum and maximum values. WLM-Stata - Summarize Internet Guide to Stata ![]()
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