Difference between revisions of "ISSS608 2017-18 T3 Assign Aakanksha Kumari Data Preparation"
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<div style="font-family:Palatino Linotype; border-radius: 1px "> <big> | <div style="font-family:Palatino Linotype; border-radius: 1px "> <big> | ||
− | All provided data files have the same format. The data are provided in comma-separated format with four columns: </big></div> | + | All provided data files have the same format. The data are provided in comma-separated format with four columns: |
+ | |||
+ | {| class="wikitable style="margin: auto;" | ||
+ | |- | ||
+ | ! Column Name!! Description | ||
+ | |- | ||
+ | | Source|| Contains the company ID# for the person who called, sent an email, purchased something, or invited people to a meeting | ||
+ | |- | ||
+ | | Etype || Contains a number designating what kind of connection is made | ||
+ | a. 0 is for calls | ||
+ | b. 1 is for emails | ||
+ | c. 2 is for purchases | ||
+ | d. 3 is for meetings | ||
+ | |||
+ | |- | ||
+ | | Destination || Information on suspicious purchases | ||
+ | |- | ||
+ | | Suspicious_meetings.csv|| Contains company ID# for the person who is receiving a call, receiving an email, selling something to a buyer, or being invited to a meeting | ||
+ | |- | ||
+ | | Time stamp|| In seconds starting on May 11, 2015 at 14:00. | ||
+ | |} | ||
+ | |||
+ | </big></div> | ||
− | |||
|} | |} | ||
Revision as of 00:10, 8 July 2018
MC Challenge 3
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Data Set
The Kasios Insider has provided data from across the company. There are call records, emails, purchases, and meetings. The data only includes the source of each transaction, the recipient (destination), and the time of the transaction. Contents of emails or phone calls are not available.
There are four data files that contain information about individuals that the Insider has indicated as suspicious:
All provided data files have the same format. The data are provided in comma-separated format with four columns:
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Tools
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Data Prep
Converting the Time in all the CSV’s from seconds to the standard format and baselining the time w.r.t May 11, 2015 at 14:00. Using Python datetime and panda’s library the modification was done. |