original_docstring: Create a dictionary with column names as keys and new column dictionaries holding
          each column's typing information as values.
docstring: Create a dictionary with column names as keys and new column dictionaries holding
  each column's typing information as values.
docstring_tokens: Create a dictionary with column names as keys and new column dictionaries holding each column ' s typing information as values .
code: def _create_columns(
          self,
          column_names,
          logical_types,
          semantic_tags,
          use_standard_tags,
          column_descriptions,
          column_origins,
          column_metadata,
          validate,
      ):
          """Create a dictionary with column names as keys and new column dictionaries holding
          each column's typing information as values."""
          columns = {}
          for name in column_names:
              semantic_tags_for_col = _convert_input_to_set(
                  (semantic_tags or {}).get(name),
                  error_language=f"semantic_tags for {name}",
                  validate=validate,
              )
              if validate:
                  _validate_not_setting_index_tags(semantic_tags_for_col, name)
              description = (column_descriptions or {}).get(name)
              origin = (
                  column_origins
                  if isinstance(column_origins, str)
                  else (column_origins or {}).get(name)
              )
              metadata_for_col = (column_metadata or {}).get(name)
  
              columns[name] = ColumnSchema(
                  logical_type=logical_types.get(name),
                  semantic_tags=semantic_tags_for_col,
                  use_standard_tags=use_standard_tags.get(name),
                  description=description,
                  origin=origin,
                  metadata=metadata_for_col,
                  validate=validate,
              )
          return columns
code_tokens: def _create_columns ( self , column_names , logical_types , semantic_tags , use_standard_tags , column_descriptions , column_origins , column_metadata , validate , ) : columns = { } for name in column_names : semantic_tags_for_col = _convert_input_to_set ( ( semantic_tags or { } ) . get ( name ) , error_language = f"semantic_tags for {name}" , validate = validate , ) if validate : _validate_not_setting_index_tags ( semantic_tags_for_col , name ) description = ( column_descriptions or { } ) . get ( name ) origin = ( column_origins if isinstance ( column_origins , str ) else ( column_origins or { } ) . get ( name ) ) metadata_for_col = ( column_metadata or { } ) . get ( name ) columns [ name ] = ColumnSchema ( logical_type = logical_types . get ( name ) , semantic_tags = semantic_tags_for_col , use_standard_tags = use_standard_tags . get ( name ) , description = description , origin = origin , metadata = metadata_for_col , validate = validate , ) return columns
short_docstring: Create a dictionary with column names as keys and new column dictionaries holding
  each column's typing information as values.
short_docstring_tokens: Create a dictionary with column names as keys and new column dictionaries holding each column ' s typing information as values .
comment: """Create a dictionary with column names as keys and new column dictionaries holding
          each column's typing information as values."""