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  3. Phase 2: Agricultural Commodity Loss: Missing Data Examination

 

In Phase 2 of our examination of agricultural insurance loss across the Palouse region of the Pacific Northwest, we explore missing data that exists in an RMarkdown document.  Missing data may be actual missing information (there are NO data existing for a particular factor), or the data may actually be a zero value (meaning that data exists for a particular factor, but in a certain county, year, or damage cause, there happened to be no insurance claims that month – even though a particular commodity is being grown).  The distinction between these two aspects is important:  We want to retain data that are actual zeros – and remove those that are truly missing datasets.  This RMarkdown document reviews missing data by exploring two factors at the same time.