Kezdi.jl is a Julia package for data manipulation and analysis. It is inspired by Stata, but it is written in Julia, which makes it faster and more flexible. It is designed to be used in the Julia REPL, but it can also be used in Jupyter notebooks or in scripts.

DNV(f(x))

Indicate that the function f should not be vectorized. The name DNV is only used for parsing, do not call it directly.

distinct(x::AbstractVector) = unique(x)

Convenience function to get the distinct values of a vector.

getdf() -> AbstractDataFrame

Return the global data frame.

rowcount(x::AbstractVector) = length(collect(skipmissing(x)))

Count the number of non-missing values in a vector.

setdf(df::Union{AbstractDataFrame, Nothing})

Set the global data frame.

@collapse y1 = expr1 y2 = expr2 ... [@if condition], [by(group1, group2, ...)]

Collapse df by evaluating expressions expr1, expr2, etc. If condition is provided, the operation is executed only on rows for which the condition is true. If by is provided, the operation is executed by group.

@count if condition]

Count the number of rows for which the condition is true. If condition is not provided, the total number of rows is counted.

@drop y1 y2 ...

or @drop if condition]

Drop the variables y1, y2, etc. from df. If condition is provided, the rows for which the condition is true are dropped.

@egen y1 = expr1 y2 = expr2 ... [@if condition], [by(group1, group2, ...)]

Generate new variables in df by evaluating expressions expr1, expr2, etc. If condition is provided, the operation is executed only on rows for which the condition is true. When the condition is false, the variables will be missing. If by is provided, the operation is executed by group.

@generate y = expr [@if condition]

Create a new variable y in df by evaluating expr. If condition is provided, the operation is executed only on rows for which the condition is true. When the condition is false, the variable will be missing.

@head [n]

Display the first n rows of the data frame. By default, n is 5.

@keep y1 y2 ... [@if condition]

Keep only the variables y1, y2, etc. in df. If condition is provided, only the rows for which the condition is true are kept.

@list

Display the entire data frame.

@names

Display the names of the variables in the data frame.

@order y1 y2 ... [desc] [last] [after=var] [before=var] [alphabetical]

Reorder the variables y1, y2, etc. in the data frame. By default, the variables are ordered in the order they are listed. If desc is provided, the variables are ordered in descending order. If last is provided, the variables are moved to the end of the data frame. If after is provided, the variables are moved after the variable var. If before is provided, the variables are moved before the variable var. If alphabetical is provided, the variables are ordered alphabetically.

@regress y x1 x2 ... [@if condition], [robust] [cluster(var1, var2, ...)]

Estimate a regression model in df with dependent variable y and independent variables x1, x2, etc. If condition is provided, the operation is executed only on rows for which the condition is true. If robust is provided, robust standard errors are calculated. If cluster is provided, clustered standard errors are calculated.

@rename oldname newname

Rename the variable oldname to newname in the data frame.

@replace y = expr [@if condition]

Replace the values of y in df with the result of evaluating expr. If condition is provided, the operation is executed only on rows for which the condition is true. When the condition is false, the variable will be left unchanged.

@sort y1 y2 ...

Sort the data frame by the variables y1, y2, etc. in ascending order.

@summarize y [@if condition]

Summarize the variable y in df. If condition is provided, the operation is executed only on rows for which the condition is true.

@tabulate y1 y2 ... [@if condition]

Create a frequency table for the variables y1, y2, etc. in df. If condition is provided, the operation is executed only on rows for which the condition is true.

@tail [n]

Display the last n rows of the data frame. By default, n is 5.

@use "filename.dta"

Read the data from the file filename.dta and set it as the global data frame.