Data-Anonymization-Tool | online application and the offline tool

Data-Anonymization-Tool is a Python library. Data-Anonymization-Tool has no bugs, it has no vulnerabilities and it has low support. However Data-Anonymization-Tool build file is not available. You can download it from GitHub.

there is an overlap of fields that you’ll see on online application and the offline tool. following describes what these fields represent and how you should go about populating them (in the offline tool, i.e.) :. field name | default value | comment(s) :-----------------: | :-------------------------: | :----------: input file’s path | input/census-income_1k.txt | the sample input file can be viewed at the default location - as stated in the default value column. if you intend to anonymize a dataset of your choice, you should provide the entire path of your dataset in the field. output file’s name | output/output-(algorithm).txt | the output is generated in the folder named output with name of the resulting dataset defined as output-(algorithm)*_(format type).txt . also, should you feed a custom value to this field, make sure that the name is in format : (name).(some-extension) - there has to be a . in the output file’s name for generating generalized dataset in *anatomy format. separator | , | in the sample text provided, the separator (delimiter) used for differentiating one attribute from other (in a record) is ,. txt