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Return Polars DataFrame as R data.frame

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Return Polars DataFrame as R data.frame


  int64_conversion = polars_options()\$int64_conversion


Any args pased to
int64_conversion How should Int64 values be handled when converting a polars object to R?
  • “double” (default) converts the integer values to double.
  • “bit64” uses bit64::as.integer64() to do the conversion (requires the package bit64 to be attached).
  • “string” converts Int64 values to character.


An R data.frame

Conversion to R data types considerations

When converting Polars objects, such as DataFrames to R objects, for example via the generic function, each type in the Polars object is converted to an R type. In some cases, an error may occur because the conversion is not appropriate. In particular, there is a high possibility of an error when converting a Datetime type without a time zone. A Datetime type without a time zone in Polars is converted to the POSIXct type in R, which takes into account the time zone in which the R session is running (which can be checked with the Sys.timezone() function). In this case, if ambiguous times are included, a conversion error will occur. In such cases, change the session time zone using Sys.setenv(TZ = "UTC") and then perform the conversion, or use the $dt$replace_time_zone() method on the Datetime type column to explicitly specify the time zone before conversion.

# Due to daylight savings, clocks were turned forward 1 hour on Sunday, March 8, 2020, 2:00:00 am
# so this particular date-time doesn't exist
non_existent_time = as_polars_series("2020-03-08 02:00:00")\$str\$strptime(pl\$Datetime(), "%F %T")

  new = c(TZ = "America/New_York"),
      # This causes an error due to the time zone (the `TZ` env var is affected).
      error = function(e) e
#> <error: in to_r: ComputeError(ErrString("datetime '2020-03-08 02:00:00' is non-existent in time zone 'America/New_York'. You may be able to use `non_existent='null'` to return `null` in this case.")) When calling: devtools::document()>

  new = c(TZ = "America/New_York"),
    # This is safe.
#> [1] "2020-03-08 02:00:00 UTC"



df = pl$DataFrame(iris[1:3, ])
#>   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
#> 1          5.1         3.5          1.4         0.2  setosa
#> 2          4.9         3.0          1.4         0.2  setosa
#> 3          4.7         3.2          1.3         0.2  setosa