title: How to perform clustering on data with time variant and time invariant attributes, in R?
body: <p>The data looks something like the example table below. I am using R to do the clustering.</p>
  
  <p>TIV: Time invariant data<br>
  TV: Time variant data</p>
  
  <p>location | population | TIV2 | Q1_TV1 | Q2_TV1 | Q3_TV1 | Q4_TV1 | Q1_TV2 | Q2_TV2 | Q3_TV2<br>
  A ..........|............. 30 |..... 9 |.......... 25 |......... 35 |.......... 22 |......... 15 |......... 20 |.......... 30 |......... 10<br>
  B ..........|............. 35 |..... 7 |.......... 38 |......... 13 |.......... 35 |......... 17 |......... 23 |.......... 34 |........... 8<br>
  C ..........|............. 32 |..... 5 |.......... 24 |......... 39 |.......... 21 |......... 19 |......... 23 |.......... 27 |......... 13    </p>
  
  <p>I have a dataset with unique locations for every row (location), a few variables whose values remain constant over time (population, TIV2) and a few variables whose values change quarterly (Q1_TV1 - Q4_TV1 and Q1_TV2 - Q4_TV2, etc.).</p>
  
  <p>I want to cluster the data to find similar locations using the time invariant and time variant data. I am aware there are packages for clustering time series data, such as TSclust. However, I am not sure if TSclust will create a distance matrix with both types of data included.</p>
  
  <p>I may have the wrong approach entirely to cluster the data I have.</p>