Difference between revisions of "Data Preparation Q2 Sumalika"

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(Created page with "''' Data Pre-Processing: ''' <br/> '''Dataset:''' Sensor Data <br/> '''Tools & Techniques:''' <br/> 1. JMP <br/> 2. Tableau <br/> 3. Excel <br/> '''1. Check for Missing Va...")
 
 
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<font size = 5; color="#001a66"><span style="font-family:Century Gothic;">ISSS608: Visual Analytics and Applications</span></font>
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<font size = 5; color="#001a66"><span style="font-family:Century Gothic;">VAST CHALLENGE 2017 </span></font>
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<font size = 4; color="#001a66"><span style="font-family:Century Gothic;"> '''- SUMALIKA KODUMURU''' </span></font>
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[[ISSS608 2016-17 T3 Assign SUMALIKA KODUMURU| <font color="#FFFFFF">Assignment Overview</font>]]
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[[Data Overview| <font color="#FFFFFF"> Data Overview </font>]]
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[[Question1_SUMALIKA KODUMURU| <font color="#FFFFFF"> Sensor Performance </font>]]
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[[Question 2_SUMALIKA KODUMURU| <font color="#FFFFFF"> Patterns of Chemical Release </font>]]
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[[Question 3_SUMALIKA KODUMURU| <font color="#FFFFFF"> Factories Responsible </font>]]
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[[References & Feedback | <font color="#FFFFFF"> References & Feedback </font>]]
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[[Question 2_SUMALIKA KODUMURU | <font color="#b30000"> '''Go back to Analysis'''</font>]]
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''' Data Pre-Processing: '''
 
''' Data Pre-Processing: '''
  
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[[File:Sumalika_Q1DP2.JPG|100%]]
 
[[File:Sumalika_Q1DP2.JPG|100%]]
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'''Data Transformation '''
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To identify the correlations between each chemical transform the data using Pivot function in Excel. The data for this plot is transformed as below:
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[[File:Sumalika_Q2DP1.JPG|100%]]
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Latest revision as of 12:54, 16 July 2017

ISSS608: Visual Analytics and Applications
VAST CHALLENGE 2017
- SUMALIKA KODUMURU

Assignment Overview

Data Overview

Sensor Performance

Patterns of Chemical Release

Factories Responsible

References & Feedback

 


Go back to Analysis

 


Data Pre-Processing:


Dataset: Sensor Data
Tools & Techniques:
1. JMP
2. Tableau
3. Excel


1. Check for Missing Values in the given data set:
The Sensor data set given by VAST and it consists of no missing values.

2. Check for Duplicate Values:
Since there is no unique identifier, no issue of duplicate values.
The date field has 1 value for each, hence no repetitions in date value.

3. Analyse variable distributions:

Date: Refers to date fields for Months April, August and December

100%


Chemical: Almost equal in number with a maximum count of AGOG-3A and minimum count of Methylosmolene

100%


Monitor: A total of 9 sensors are located around the Factories.

100%


Data Transformation
To identify the correlations between each chemical transform the data using Pivot function in Excel. The data for this plot is transformed as below:
100%