Data inaccuracies and Python libraries for data quality eval…

All organizations expect the analysis of their operations to be accurate and valid. In the module readings, you learned about how the data industry has developed different dimensions that define data quality. You were also introduced to three important Python libraries: pandas, NumPy, and Matplotlib. In this discussion, you will draw from what you have learned to evaluate the impacts of data inaccuracies on specific industries and the value of Python libraries for evaluating data quality issues. In your initial post, address the following: Identify a specific reason for inaccuracies in data and how it can impact an organization in an industry of your choosing. What are the implications of the data error for that industry? Pick one of the Python libraries you worked with in this module and discuss how it can be used to evaluate data quality issues. Provide an example function that you would use to correct a specific issue with the data set.