Difference between revisions of "DataPreparation"
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==Excluding & Hiding Data== | ==Excluding & Hiding Data== | ||
After the above steps, choose the key words and label all the rows related to these 13 key words. And then invert selection to exclude and hide the rows which do not include all the key words. | After the above steps, choose the key words and label all the rows related to these 13 key words. And then invert selection to exclude and hide the rows which do not include all the key words. | ||
| − | <gallery heights=" | + | <gallery heights="170" widths="1000"> |
File:ZW Exclude&Hide.JPG|Figure : Key Words | File:ZW Exclude&Hide.JPG|Figure : Key Words | ||
</gallery> | </gallery> | ||
Revision as of 00:22, 15 October 2017
ISSS608 Visual Analytics and Applications Assignment
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Contents
Data Preparation
Transforming data
After imported the original dataset into JMP, found that two columns are dirty data which need to be cleaned. Splitting the column "Created_at" into two columns, one is "Date" and the other one is "Time". With the same method split the column "location" into "latitude" and "longitude".
Figure : Dirty Data Columns
Key Words Selection
By reading requirement of the assignment, there are lots of the key words. With the function of Text Explorer in JMP, also found that the key words list. The top 5 key words in the list are all related to illness.
Figure : Key Words
Combined all the resources, finally choose 13 key words in the report.
Excluding & Hiding Data
After the above steps, choose the key words and label all the rows related to these 13 key words. And then invert selection to exclude and hide the rows which do not include all the key words.
Figure : Key Words
