Tools for Easily Combining and Cleaning Data Sets.

DataCombine

Christopher Gandrud

Version 0.2.21

Please report any bugs or suggestions at: https://github.com/christophergandrud/DataCombine/issues.

Motivation and Functions

DataCombine is a set of miscellaneous tools intended to make combining data sets--especially time-series cross-section data--easier. The package is continually being developed as I turn lines of code that I frequently use into single functions. It currently includes the following functions:

• CasesTable function added to report cases after listwise deletion of missing values for time-series cross-sectional data.

• change: calculates the absolute, percentage, and proportion change from a specified lag, including within groups.

• CountSpell: function that returns a variable counting the spell number for an observation. Works with grouped data.

• dMerge: merges 2 data frames and report/drop/keeps only duplicates.

• DropNA: drops rows from a data frame when they have missing (NA) values on a given variable(s).

• FillDown: fills in missing (NA) values with the previous non-missing value

• FillIn: fills in missing values of a variable from one data frame with the values from another variable.

• FindDups: find duplicated values in a data frame and subset it to either include or not include them.

• FindReplace: replaces multiple patterns found in a character string column of a data frame.

• grepl.sub: subsets a data frame if a specified pattern is found in a character string.

• InsertRow: allows user to insert a row into a data frame. Largely implements: Ari B. Friedman's function.

• MoveFront: moves variables to the front of a data frame. This can be useful if you have a data frame with many variables and want to move a variable or variables to the front.

• NaVar: create new variable(s) indicating if there are missing values in other variable(s).

• shift: creates lag and lead variables, including for time-series cross-sectional data. The shifted variable is returned to a new vector. This function is largely based on TszKin Julian's shift function.

• slide: creates lag and lead variables, including for time-series cross-sectional data. The slid variable are added to the original data frame. This expands the capabilities of shift.

• slideMA: creates a moving average for a period before or after each time point for a given variable.

• SpreadDummy: spread a dummy variable (1's and 0') over a specified time period and for specified groups.

• StartEnd: finds the starting and ending time points of a spell, including for time-series cross-sectional data.

• rmExcept: removes all objects from a workspace except those specified by the user.

• TimeExpand: expands a data set so that it includes an observation for each time point in a sequence. Works with grouped data.

• TimeFill: creates a continuous Unit-Time-Dummy data frame from a data frame with Unit-Start-End times.

• VarDrop: drops one or more variables from a data frame.

Updates

I will continue to add to the package as I build data sets and run across other pesky tasks I do repeatedly that would be simpler if they were completed by a single function.

Installation

DataCombine is on CRAN.

You can also install the most recent stable version with install_github from the devtools:

devtools::install_github('christophergandrud/DataCombine')