November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Harmonization
With data harmonization, the data scientist converts, translates, or maps data values to other more desirable values, based upon the overall objective or purpose of the analysis to be performed. The most common examples of this can be gender or country code. For example, if your file has gender coded as 1s and 0s or M and F, you might want to convert the data points to be consistently coded as MALE or FEMALE.
With country codes, the data scientist may want to plot summations for regions: North America, South America, and Europe rather than USA, CA, MX, BR, CH, GB, FR, and DE individually. In this case, he or she would be creating aggregated values:
North America = USA + CA + MX
South America = BR + CH
Europe = GB + FR + DE
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