GH-15947: fix R test error message change, fix Python column_names co…

…ntain only columns not skipped.

h2o-py/h2o/h2o.py

@@ -871,11 +871,10 @@ def parse_setup(raw_frames, destination_frame=None, header=0, separator=None, co
     if column_names is not None: # used when python object is converted to H2O Frame 
         if not isinstance(column_names, list): raise ValueError("col_names should be a list")
         if (skipped_columns is not None) and len(skipped_columns)>0:
-         #   if ((len(column_names)-len(skipped_columns)) != parse_column_len) and (len(column_names) != parse_column_len):
-         if (len(column_names)-len(skipped_columns)) != parse_column_len:
+         if len(column_names) != parse_column_len:
                 raise ValueError(
                     "length of col_names minus length of skipped_columns should equal the number of columns parsed: "
-                    "%d vs %d" % ((len(column_names)-len(skipped_columns), parse_column_len)))
+                    "%d vs %d" % (len(column_names), parse_column_len))
         else: # no skipped columns here
             if len(column_names) != len(j["column_types"]): raise ValueError(
                 "length of col_names should be equal to the number of columns: %d vs %d"

h2o-r/tests/testdir_jira/runit_hexdev_29_import_types.R

@@ -11,6 +11,7 @@ source("../../scripts/h2o-r-test-setup.R")
 test.continuous.or.categorical <- function() {
   df.hex <- h2o.uploadFile(locate("smalldata/jira/hexdev_29.csv"),
     col.types = c("enum", "enum", "enum"))
+  browser()
 
   expect_true(is.factor(df.hex$h1))
   expect_true(is.factor(df.hex$h2))
@@ -36,7 +37,7 @@ test.continuous.or.categorical <- function() {
 
   e <- tryCatch(h2o.importFile(locate("smalldata/iris/iris.csv"), col.names=c("C1","C2","C3","C4","C5","C6"),
                                col.types=list(by.col.name=c("C4"),types=c("Enum"))), error = function(x) x)
-  expect_true(e[[1]] == "length of col.names must equal to the number of columns in dataset")
+  expect_true(e[[1]] == "length of col.names (minus length of skipped_columns if present) must equal to the number of columns in dataset")
 
   # col.types as character vector
   df.hex2 <- h2o.importFile(locate("smalldata/iris/iris.csv"), col.types=c("Numeric","Numeric","Enum","Numeric","Enum"))