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.

ismissing(args...) -> Bool

Return true if any of the arguments is missing.

cond(x, y, z)

Return y if x is true, otherwise return z. If x is a vector, the operation is vectorized. This function mimics x ? y : z, which cannot be vectorized.

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

Convenience function to get the distinct values of a vector.

getdf() -> AbstractDataFrame

Return the global data frame.

keep_only_values(x::AbstractVector) -> AbstractVector

Return a vector with only the values of x, excluding any missingvalues,nothings,Infa andNaN`s.

rowcount(x::AbstractVector) = length(keep_only_values(x))

Count the number of valid values in a vector.

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

Set the global data frame.

@append "filename.dta"

Append the data from the file filename.dta to the global data frame. Columns that are not common filled with missing values.

@clear

Clears the global dataframe.

@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.

@describe [y1] [y2]...

Show the names and data types of columns of the data frame. If no variable names given, all are shown.

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

Display the entire data frame or the rows for which the condition is true. If variable names are provided, only the variables in the list are displayed.

@mvencode y1 y2 [_all] ... [if condition], [mv(value)]

Encode missing values in the variables y1, y2, etc. in the data frame. If condition is provided, the operation is executed only on rows for which the condition is true. If mv is provided, the missing values are encoded with the value value. By default value is missing making no changes on the dataframe. Using _all encodes all varibles of the DataFrame.

@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.

The regression is limited to rows for which all variables are values. Missing values, infinity, and NaN are automatically excluded.

@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.

@save "filename.dta", [replace]

Save the global data frame to the file filename.dta. If the file already exists, the replace option must be provided.

@sort y1 y2 ... , [desc]

Sort the data frame by the variables y1, y2, etc. By default, the variables are sorted in ascending order. If desc is provided, the variables are sorted in descending 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", [clear]

Read the data from the file filename.dta and set it as the global data frame. If there is already a global data frame, @use will throw an error unless the clear option is provided