Validation of Local and Remote Data Tables


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Documentation for package ‘pointblank’ version 0.3.0

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action_levels Set action levels for reacting to exceeding thresholds
all_passed Did all of the validations fully _pass_?
col_exists Do one or more columns actually exist?
col_is_character Do the columns contain character/string data?
col_is_date Do the columns contain R 'Date' objects?
col_is_factor Do the columns contain R 'factor' objects?
col_is_integer Do the columns contain integer values?
col_is_logical Do the columns contain logical values?
col_is_numeric Do the columns contain numeric values?
col_is_posix Do the columns contain 'POSIXct' dates?
col_vals_between Are numerical column data between two specified values?
col_vals_equal Are numerical column data equal to a specific value?
col_vals_gt Are numerical column data greater than a specific value?
col_vals_gte Are numerical column data greater than or equal to a specific value?
col_vals_in_set Are column data part of a specific set of values?
col_vals_lt Are numerical column data less than a specific value?
col_vals_lte Are numerical column data less than or equal to a specific value?
col_vals_not_between Are numerical column data not between two specified values?
col_vals_not_equal Are numerical column data not equal to a specific value?
col_vals_not_in_set Are data not part of a specific set of values?
col_vals_not_null Are column data not 'NULL'/'NA'?
col_vals_null Are column data 'NULL'/'NA'?
col_vals_regex Do strings in column data match a regex pattern?
conjointly Perform multiple rowwise validations for joint validity
create_agent Create a pointblank agent object
get_agent_report Get a simple report from an agent
get_data_extracts Collect data extracts from a validation step
interrogate Given an agent that has a validation plan, perform an interrogation
rows_distinct Verify that row data are distinct
rows_not_duplicated Verify that row data are not duplicated (deprecated)
small_table A small table that useful for testing