Difference between revisions of "ISSS608 2017-18 T3 Assign Wang Runyu Data Visualization"
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==Patterns of all of the bird species== | ==Patterns of all of the bird species== | ||
===Overview Patterns=== | ===Overview Patterns=== | ||
+ | The plot below indicates the birds location of all the species. All species spread over the entire preserve. Different Birds intend to form their own society | ||
[[File:Pattern overview all.png|700px]] | [[File:Pattern overview all.png|700px]] | ||
<br> | <br> |
Revision as of 23:13, 7 July 2018
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Patterns of all of the bird species
Overview Patterns
The plot below indicates the birds location of all the species. All species spread over the entire preserve. Different Birds intend to form their own society
Pattern of Different Quarter
Pattern Around Dumping Site
Q2
Visual Analytical Approach
As the text format outcome from seewave package(analyzeFolder function) contains 69 features, it is not practical for us to analyze all the features visually. In the first step, I use findCorrelation() function to eliminate highly correlated features. I set the pair-wise absolute correlation cut off to 0.6.
Correlation Plot
remove features based on corr plot observations
Corrplot, select variables, we not only consider to check the variables nearby, but all the variables For example, group of 'specSlape_sd', 'harmonics_median', 'peakFreq_median', I choose 'peakFreq_median'.