This function coerces a tibble, data.frame, or list to a pibble tibble by adding the .i, .t, and .d attributes to it.

as_pibble(x, .i = NULL, .t = NULL, .d = 1, .uniqcheck = FALSE, ...)

# S3 method for tbl_df
as_pibble(x, .i = NULL, .t = NULL, .d = 1, .uniqcheck = FALSE, ...)

# S3 method for grouped_df
as_pibble(x, .i = NULL, .t = NULL, .d = 1, .uniqcheck = FALSE, ...)

# S3 method for data.frame
as_pibble(x, .i = NULL, .t = NULL, .d = 1, .uniqcheck = FALSE, ...)

# S3 method for list
as_pibble(x, .i = NULL, .t = NULL, .d = 1, .uniqcheck = FALSE, ...)



A data frame, tibble or list


Quoted or unquoted variable(s) that identify the individual cases. If this is omitted, pibble will assume the data set is a single time series.


Quoted or unquoted variable indicating the time. pmdplyr accepts two kinds of time variables: numeric variables where a fixed distance .d will take you from one observation to the next, or, if .d=0, any standard variable type with an order. Consider using the time_variable() function to create the necessary variable if your data uses a Date variable for time.


Number indicating the gap in t between one period and the next. For example, if .t indicates a single day but data is collected once a week, you might set .d=7. To ignore gap length and assume that "one period ago" is always the most recent prior observation in the data, set .d=0. By default, .d=1.


Logical parameter. Set to TRUE to perform a check of whether .i and .t uniquely identify observations, and present a message if not. By default this is set to FALSE and the warning message occurs only once per session.


Other arguments passed on to individual methods.


  • .i, Quoted or unquoted variable(s) indicating the individual-level panel identifier

  • .t, Quoted or unquoted variable indicating the time variable

  • .d, a number indicating the gap

Note that pibble does not require that .i and .t uniquely identify the observations in your data, but it will give a warning message (a maximum of once per session, unless .uniqcheck=TRUE) if they do not.


data(SPrail) # I set .d=0 here to indicate that I don't care how large the gap # between one period and the next is. # If I want to use 'insert_date' for .t with a fixed gap between periods, # I need to transform it into an integer first; see time_variable() SP <- as_pibble(SPrail, .i = c(origin, destination), .t = insert_date, .d = 0 )
#> Note that the selected .i and .t do not uniquely identify observations in the data. #> This message will be displayed only once per session unless the .uniqcheck option is set to TRUE.
#> .i = origin, destination; .t = insert_date; .d = 0.
#> [1] TRUE
attr(SP, ".i")
#> origin destination #> "origin" "destination"
attr(SP, ".t")
#> insert_date #> "insert_date"
attr(SP, ".d")
#> [1] 0
data(Scorecard) # Here, year is an integer, so I can use it with .d = 1 to # indicate that one period is a change of one unit in year # Conveniently, .d = 1 is the default Scorecard <- as_pibble(Scorecard, .i = unitid, .t = year) is_pibble(Scorecard)
#> .i = unitid; .t = year; .d = 1.
#> [1] TRUE