Update


I tried a few things. First I eliminated the tracts we talked about and dropped the access to food variable. It dropped the number of prinicpal components to five and number of recommended classes to five. The classes made no sense to me so I reran it with the access to food varaiable, keeping the tracts we spoke of removed. The following Is the results. I need some help.

What I see are two classes that display gentrification characteristics (2 & 5). Class two appears to have stronger characteristics, however when I check out the map, class 2 appears very rural and class 5 makes sense for gentrifying neighborhoods.

Do you have any thoughts on these results, or perhaps another variable I should add?

Table of chapter one means


##                 V1        V2         V3        V4        V5        V6
## class        1.000     2.000      3.000     4.000     5.000     6.000
## y00_04     590.760    29.560    938.520   105.840   369.750    52.750
## y05_09     737.990    33.140   1225.150    91.100   428.920    27.210
## y10_14     696.750    22.030   1351.360    82.700   491.960    22.680
## y15_19    1028.070    38.150   1476.990    87.150   569.440    26.940
## pnhw00       0.167     0.563      0.804     0.453     0.388     0.295
## pnhw12       0.143     0.404      0.743     0.341     0.333     0.203
## pnhw19       0.146     0.337      0.707     0.297     0.339     0.163
## pnhb00       0.542     0.127      0.025     0.140     0.116     0.060
## pnhb12       0.488     0.162      0.025     0.144     0.096     0.056
## pnhb19       0.438     0.174      0.029     0.147     0.097     0.067
## phisp00      0.269     0.262      0.122     0.345     0.451     0.602
## phisp12      0.340     0.360      0.159     0.441     0.516     0.700
## phisp19      0.380     0.403      0.168     0.464     0.499     0.727
## mhhinc00 54643.600 96059.980 135657.440 75571.710 66133.300 60296.680
## mhhinc12 46726.270 85009.820 129389.700 62934.170 59404.160 48996.640
## mhhinc19 53572.530 87808.560 141709.840 68291.700 68058.280 53357.640
## pedu00       0.130     0.282      0.597     0.304     0.253     0.128
## pedu12       0.153     0.297      0.652     0.286     0.288     0.120
## pedu19       0.197     0.311      0.697     0.311     0.344     0.136
## pop00        7.800     7.968      8.013     8.390     8.219     8.347
## pop12        7.887     8.436      8.296     8.459     8.303     8.319
## pop19        8.046     8.564      8.412     8.558     8.411     8.378
## dev01        0.650     0.486      0.726     0.958     0.864     0.997
## dev11        0.697     0.566      0.769     0.969     0.898     0.998
## dev19        0.721     0.599      0.783     0.973     0.910     0.998
## la00         0.179     0.092      0.232     0.212     0.470     0.378
## la10         0.179     0.092      0.232     0.212     0.470     0.378
## la19         0.207     0.135      0.299     0.326     0.500     0.422

A table of the number of census tracts in each classification


## 
##   1   2   3   4   5   6 
## 107 204 160 183 277 170

Graphs


2 classifications look promising, both class 2 and 5 look promising, with 2 displaying what I would call stronger gentrifcation indications.


Access to food definitely made a difference.


### Maps of the clusters


### Austin


### Dallas


### San Antonio

Correlation of principal components


Working on the title. For this plot there were 6 principal components accounting for 87% of the variation. 6 Classes were recommended for the LPA.