Difference between revisions of "ISSS608 2017-18 T3 Assign Xie Zhimao Method"

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<b><font size = 6; color="#3a2e29"; style="font-family:Century Gothic">&emsp;&emsp;&emsp;2018 Mini-Challenge 2 Method</font></b>
 
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[[ISSS608_2017-18_T3_Assign_Xie_Zhimao_Method|<font color="#000000">Methodology</font>]]
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[[ISSS608_2017-18_T3_Assign_Xie_Zhimao_Method|<font color="#000000">Data Preparation</font>]]
  
 
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<font size = 3; color="#FFFFFF"><span style="font-family:Century Gothic;">Brief Introduction</span></font>
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<font size = 3; color="#FFFFFF"><span style="font-family:Century Gothic;">Tools Description</span></font>
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*SAS JMP Pro
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*Microsoft Excel
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*Tableau
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{| class="wikitable" style="background-color:#FFFFFF;" width="100%"
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<b>No.</b>
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<b>&emsp;Approach</b>
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<b>&emsp;&emsp;Description</b>
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1.
 +
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SAS JMP Pro<br>
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(&emsp;Data Exploration)
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*Use SAS JMP Pro to open the metadata and check the ditribution and validity of the data.<br>[[File:Zhimao3.png|500px]][[File:Zhimao4.png|500px]]
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*We found the missing data is <b>0</b> and there is no obviously unreasonable skewed distribution, so our initial clean step is complete.
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*However, when it refers to chemical units of measure, we noticed there are different units, such as mg/l and μg/l. Therefore, we need further data wrangling by use Microsoft Excel.
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2.
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Microsoft Excel<br>
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(Data Wrangling)
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||
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*Use filter and pivot table function in Microsoft Excel extract out the data we need and rename them as revised value(μg/l).
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*Given thr geographical analysis we also record the geo-code of background image in the data file.[[File:Zhimao5.png|200px]]
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|-
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|
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3.
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||
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&emsp;&emsp;Tableau<br>
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(Data Analysis)
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||
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*Import raw data into Tableau and inner join the geo-code.[[File:Zhimao6.png|500px]]
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<br>
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*From the view of trend change, we can oberserve there are two dramaticlly increase in both 2003 and 2009.
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*In addition, 2 locations were taken into consideration of sampling extraction site since 2009. Especillay in Tansanee, it always occupies the largest value of chemical contamination in recent years.<br>
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[[File:Zhimao7.png|800px|center]]
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<br>
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*To prove whether the Kasios Furniture Company caused environmental damage to the Boonsong Lekagul Wildlife Preserve, we select the sample from recent 3 years and combined them with the maps.<br>
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[[File:Zhimao8.png|800px|center]]
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<br>
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*To be specific, we would like to view the measure performances in different locations in a treemap.
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[[File:Zhimao9.png|800px|center]]
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Latest revision as of 22:02, 7 July 2018

Zhimao2.jpg    2018 Mini-Challenge 2 Method

Overview

Data Preparation

Visualization

Conclusion



Tools Description

  • SAS JMP Pro
  • Microsoft Excel
  • Tableau

No.

 Approach

  Description

1.

SAS JMP Pro
( Data Exploration)

  • Use SAS JMP Pro to open the metadata and check the ditribution and validity of the data.
    Zhimao3.pngZhimao4.png
  • We found the missing data is 0 and there is no obviously unreasonable skewed distribution, so our initial clean step is complete.
  • However, when it refers to chemical units of measure, we noticed there are different units, such as mg/l and μg/l. Therefore, we need further data wrangling by use Microsoft Excel.

2.

Microsoft Excel
(Data Wrangling)

  • Use filter and pivot table function in Microsoft Excel extract out the data we need and rename them as revised value(μg/l).
  • Given thr geographical analysis we also record the geo-code of background image in the data file.Zhimao5.png

3.

  Tableau
(Data Analysis)

  • Import raw data into Tableau and inner join the geo-code.Zhimao6.png


  • From the view of trend change, we can oberserve there are two dramaticlly increase in both 2003 and 2009.
  • In addition, 2 locations were taken into consideration of sampling extraction site since 2009. Especillay in Tansanee, it always occupies the largest value of chemical contamination in recent years.
Zhimao7.png


  • To prove whether the Kasios Furniture Company caused environmental damage to the Boonsong Lekagul Wildlife Preserve, we select the sample from recent 3 years and combined them with the maps.
Zhimao8.png


  • To be specific, we would like to view the measure performances in different locations in a treemap.
Zhimao9.png
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