Formats R objects with pander
Usage
formatter_pander(
  x,
  ...,
  .logcall = sys.call(),
  .topcall = sys.call(-1),
  .topenv = parent.frame()
)Arguments
- x
 object to be logged
- ...
 optional parameters passed to
pander- .logcall
 the logging call being evaluated (useful in formatters and layouts when you want to have access to the raw, unevaluated R expression)
- .topcall
 R expression from which the logging function was called (useful in formatters and layouts to extract the calling function's name or arguments)
- .topenv
 original frame of the
.topcallcalling function where the formatter function will be evaluated and that is used to look up thenamespaceas well vialogger:::top_env_name
See also
Other log_formatters:
formatter_cli(),
formatter_glue(),
formatter_glue_or_sprintf(),
formatter_glue_safe(),
formatter_json(),
formatter_logging(),
formatter_paste(),
formatter_sprintf()
Examples
log_formatter(formatter_pander)
log_info("42")
#> INFO [2025-10-30 21:00:46] 42
log_info(42)
#> INFO [2025-10-30 21:00:47] _42_
log_info(4 + 2)
#> INFO [2025-10-30 21:00:47] _6_
log_info(head(iris))
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47] -------------------------------------------------------------------
#> INFO [2025-10-30 21:00:47]  Sepal.Length   Sepal.Width   Petal.Length   Petal.Width   Species 
#> INFO [2025-10-30 21:00:47] -------------- ------------- -------------- ------------- ---------
#> INFO [2025-10-30 21:00:47]      5.1            3.5           1.4            0.2       setosa  
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]      4.9             3            1.4            0.2       setosa  
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]      4.7            3.2           1.3            0.2       setosa  
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]      4.6            3.1           1.5            0.2       setosa  
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]       5             3.6           1.4            0.2       setosa  
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]      5.4            3.9           1.7            0.4       setosa  
#> INFO [2025-10-30 21:00:47] -------------------------------------------------------------------
#> INFO [2025-10-30 21:00:47] 
log_info(head(iris), style = "simple")
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]  Sepal.Length   Sepal.Width   Petal.Length   Petal.Width   Species 
#> INFO [2025-10-30 21:00:47] -------------- ------------- -------------- ------------- ---------
#> INFO [2025-10-30 21:00:47]      5.1            3.5           1.4            0.2       setosa  
#> INFO [2025-10-30 21:00:47]      4.9             3            1.4            0.2       setosa  
#> INFO [2025-10-30 21:00:47]      4.7            3.2           1.3            0.2       setosa  
#> INFO [2025-10-30 21:00:47]      4.6            3.1           1.5            0.2       setosa  
#> INFO [2025-10-30 21:00:47]       5             3.6           1.4            0.2       setosa  
#> INFO [2025-10-30 21:00:47]      5.4            3.9           1.7            0.4       setosa  
#> INFO [2025-10-30 21:00:47] 
log_info(lm(hp ~ wt, mtcars))
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47] ----------------------------------------------------------------
#> INFO [2025-10-30 21:00:47]               Estimate   Std. Error   t value    Pr(>|t|)  
#> INFO [2025-10-30 21:00:47] ----------------- ---------- ------------ ---------- -----------
#> INFO [2025-10-30 21:00:47]  **(Intercept)**    -1.821      32.32      -0.05633    0.9555   
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47]      **wt**         46.16       9.625       4.796     4.146e-05 
#> INFO [2025-10-30 21:00:47] ----------------------------------------------------------------
#> INFO [2025-10-30 21:00:47] 
#> INFO [2025-10-30 21:00:47] Table: Fitting linear model: hp ~ wt
#> INFO [2025-10-30 21:00:47] 
