ISSS608 2016-17 T3 Assign GAURAV MIGLANI DataPrep

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Tools and Techniques Used

1. JMP
2. Tableau
3. Microsoft Excel

Dataset and Description

There are two datasets provided to us by VAST Challenge. The first dataset gives us the information about the locations and the readings taken over time in that location. The second dataset gives us information regarding the units of each of the measure recorded. The 5 important variables in the raw dataset have been summarized in the table below:

Variable Name Description
Id Identification number for the record
Value Measured value for the chemical or property in this record
Location Name of the location sample was taken from.
Sample Date Date sample was taken from the location
Measure Chemicals (e.g., Sodium) or water properties (e.g., Water temperature) measured in the record


Waterways Map

The map indicates the approximate location of the dumping site along with different location where water contamination might have occurred by Kasios due to release of some toxic chemicals.

Waterways Final.jpg

Geospatial Data

We prepared the Geo-spatial data by creating two additional columns in the dataset that was provided to us for the VAST Challenge. The columns created represents the coordinates of each of the location that can be plotted on a 200x200 grid. The flow chart below shows the data preparation and methodology used for preparing geospatial visualisation.

Left

Joining the Datasets

After the creating the coordinates column, it was necessary to join the two datasets so that it can be used in Tableau for visualisation.

Joining.png

The two datasets were imported in tableau and the inner join was performed to have one complete dataset for investigation. The inner join was done on measure variable as shown: -

Left

Methodology and Visualisations

Description Illustration
1.Line Graphs showing the change over time


The line graphs have been used to visualaise how different chemicals are spread out across locations and how the chemical content has changed over time.Through line graph we are able to unfold the past and the most recent situation with respect to the chemical contamination in the Boonsong Lekagul waterways. Also, we have filtered out some the chemicals which have not shown a significant change over time across all locations.Morover,there are chemicals which are not present for a long period of time have also been filtered out.

Line1.png
2.Heat Map showing the pattern in chemical contamination


For a more rigid analysis,i have created heat maps to analyse how different chemicals show a certain pattern in the values.In order to investigate if there has been any dumping and increase in chemical contamination,i have only taken the recent 2 years of data to figure out any pattern, if any.

Heat1.png
4.Anomolies using Box Plot


We observed that there are few anamolies in the dataset provided to us which revolve particularly around the location Tansanee,Decha,Sakda and Kannika.I have tried to unfold the abnormal behaviour by showing the change with the help of a Box-Plot.

BoxPlot.png
3.Waterways Map


The Map provided is all about the Location which might have been contaminated by release of chemicals by Kasios. The map reflects the amount of chemical that is dominant in a particular location in year 2015-2016.
The chemicals are reflected by the pie charts. Here, i have only shown the chemicals that are present in large amount in each of the locations.

Maps.png