Reshape

Start with the expanded example for each command. Open the variants for options and alternative R approaches. Read the qualifications before adapting the code.

reshape

Wide to long

Stata

reshape long var, i(id) j(year)

R tidyr

tidyr::pivot_longer(data, tidyselect::starts_with("var"), names_to = "year", names_prefix = "var", names_transform = list(year = as.integer), values_to = "var")

Differs from Stata Converts numeric suffixes to integer year values, matching reshape long without string. pivot_longer() returns a text year without names_transform and does not enforce reshape i()/j() uniqueness constraints.

Stata reference · R reference

Long to wide

Stata

reshape wide var, i(id) j(year)

R tidyr

pivot_wider(data, names_from = year, values_from = var, names_prefix = "var")

Differs from Stata Duplicate keys can create list-columns in pivot_wider(); Stata reshape wide rejects duplicate i()/j() combinations. Validate keys first.

Stata reference · R reference

2 more examples and alternatives

Reshape repeated measurements to long form with base R

Stata

reshape long var, i(id) j(year)

R stats

stats::reshape(data, direction = "long", varying = list(c("var2000", "var2001")), v.names = "var", timevar = "year", times = c(2000, 2001), idvar = "id")

Differs from Stata Explicitly list the wide columns and time values. This fixed workflow uses var2000 and var2001; adapt those names to your data.

Stata reference · R reference

Reshape repeated measurements to wide form with base R

Stata

reshape wide var, i(id) j(year)

R stats

stats::reshape(data, direction = "wide", v.names = "var", timevar = "year", idvar = "id", sep = "")

Differs from Stata Requires one row per id/year combination. R row ordering and attributes differ from Stata; compare keys and values explicitly.

Stata reference · R reference

xpose

Transpose the data

Stata

xpose, clear

R tibble

tibble::as_tibble(t(data), .name_repair = "unique")

Stata reference · R reference