Difference between revisions of "IS428 AY2019-20T1 Assign Chua Xuan Ni, Rachel DATA TRANSFORMATION"
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== Dataset Analysis & Transformation Process == | == Dataset Analysis & Transformation Process == | ||
| − | '''Issue 1:''' In the current dataset, “mc1-reports-data.csv”. The different categories of damage are a column by itself, making it difficult to compare the damage by the categories. | + | '''Issue 1:''' |
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| + | In the current dataset, “mc1-reports-data.csv”. The different categories of damage are a column by itself, making it difficult to compare the damage by the categories. | ||
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Solution: Pivot the different categories of damage – sewer_and_water, power, roads_and_bridges, medical and buildings into a new column, “Damage Area”, with their respective damage level in a new column, “Damage Level (0-10)”. | Solution: Pivot the different categories of damage – sewer_and_water, power, roads_and_bridges, medical and buildings into a new column, “Damage Area”, with their respective damage level in a new column, “Damage Level (0-10)”. | ||
Revision as of 19:15, 11 October 2019
IS428 VAST 2019 Mini Challenge 1
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Dataset Analysis & Transformation Process
Issue 1:
In the current dataset, “mc1-reports-data.csv”. The different categories of damage are a column by itself, making it difficult to compare the damage by the categories.
Solution: Pivot the different categories of damage – sewer_and_water, power, roads_and_bridges, medical and buildings into a new column, “Damage Area”, with their respective damage level in a new column, “Damage Level (0-10)”.
To do this, I used Tableau Prep’s “Pivot function” to make the changes. After applying the pivot function, you can see that I now have 2 new columns containing the data from sewer_and_water, power, roads_and_bridges, medical and buildings merged as one.
