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Welcome to GDPVotes!

library(GDPVoters)

States<-getGDP(filepath="./data/lagdp1219.xlsx")
print(States[["Louisiana"]])
## # A tibble: 64 x 10
##    county   `2015`   `2016`  `2017` `2018` rTotal c2016      c2017 c2018 rChange
##    <chr>    <chr>     <dbl>   <dbl>  <dbl> <chr>  <chr>      <dbl> <dbl> <chr>  
##  1 Acadia   1596865  1.59e6  1.59e6 1.60e6 30     -0.2         0     0.6 40     
##  2 Allen    591149   6.16e5  6.29e5 6.31e5 45     4.0999999~   2.2   0.2 43     
##  3 Ascensi~ 8200541  7.92e6  8.31e6 8.60e6 9      -3.4         4.9   3.5 17     
##  4 Assumpt~ 439467   4.07e5  4.39e5 4.54e5 53     -7.5         7.9   3.5 18     
##  5 Avoyell~ 828797   8.34e5  8.54e5 8.48e5 40     0.6          2.4  -0.7 54     
##  6 Beaureg~ 916684   9.08e5  9.02e5 9.22e5 37     -0.9        -0.6   2.2 26     
##  7 Bienvil~ 614943   6.13e5  7.06e5 7.44e5 43     -0.3        15     5.5 6      
##  8 Bossier  5515885  5.44e6  5.59e6 5.81e6 11     -1.4         2.9   3.9 13     
##  9 Caddo    129249~  1.29e7  1.31e7 1.33e7 6      -0.5         1.6   1.7 31     
## 10 Calcasi~ 126886~  1.32e7  1.39e7 1.44e7 4      3.8          5.3   3.8 15     
## # ... with 54 more rows
LA_GDP<-getStateGDP("Louisiana")
print(LA_GDP)
## # A tibble: 64 x 10
##    county   `2015`   `2016`  `2017` `2018` rTotal c2016      c2017 c2018 rChange
##    <chr>    <chr>     <dbl>   <dbl>  <dbl> <chr>  <chr>      <dbl> <dbl> <chr>  
##  1 Acadia   1596865  1.59e6  1.59e6 1.60e6 30     -0.2         0     0.6 40     
##  2 Allen    591149   6.16e5  6.29e5 6.31e5 45     4.0999999~   2.2   0.2 43     
##  3 Ascensi~ 8200541  7.92e6  8.31e6 8.60e6 9      -3.4         4.9   3.5 17     
##  4 Assumpt~ 439467   4.07e5  4.39e5 4.54e5 53     -7.5         7.9   3.5 18     
##  5 Avoyell~ 828797   8.34e5  8.54e5 8.48e5 40     0.6          2.4  -0.7 54     
##  6 Beaureg~ 916684   9.08e5  9.02e5 9.22e5 37     -0.9        -0.6   2.2 26     
##  7 Bienvil~ 614943   6.13e5  7.06e5 7.44e5 43     -0.3        15     5.5 6      
##  8 Bossier  5515885  5.44e6  5.59e6 5.81e6 11     -1.4         2.9   3.9 13     
##  9 Caddo    129249~  1.29e7  1.31e7 1.33e7 6      -0.5         1.6   1.7 31     
## 10 Calcasi~ 126886~  1.32e7  1.39e7 1.44e7 4      3.8          5.3   3.8 15     
## # ... with 54 more rows

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