## # A tibble: 6,497,651 x 6
## fips scc pollutant emissions type year
## <chr> <chr> <chr> <dbl> <fct> <fct>
## 1 09001 10100401 PM25-PRI 15.7 POINT 1999
## 2 09001 10100404 PM25-PRI 234. POINT 1999
## 3 09001 10100501 PM25-PRI 0.128 POINT 1999
## 4 09001 10200401 PM25-PRI 2.04 POINT 1999
## 5 09001 10200504 PM25-PRI 0.388 POINT 1999
## 6 09001 10200602 PM25-PRI 1.49 POINT 1999
## 7 09001 10200603 PM25-PRI 0.2 POINT 1999
## 8 09001 10300401 PM25-PRI 0.081 POINT 1999
## 9 09001 10300501 PM25-PRI 0.184 POINT 1999
## 10 09001 10300504 PM25-PRI 0.273 POINT 1999
## # ... with 6,497,641 more rows
This is document uses base R and GGPlot2 to graphically investigate the trend of air pollution in the US using the the dataset that measures PM2.5 in the United States by States from 1999 to 2008.
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 4 x 2
## year emissions
## <dbl> <dbl>
## 1 1999 7332967.
## 2 2002 5635780.
## 3 2005 5454703.
## 4 2008 3464206.
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 4 x 2
## year emissions
## <dbl> <dbl>
## 1 1999 4986.
## 2 2002 3586.
## 3 2005 3344.
## 4 2008 3430.
## `summarise()` regrouping output by 'year' (override with `.groups` argument)
## `geom_smooth()` using formula 'y ~ x'
## `summarise()` ungrouping output (override with `.groups` argument)
## `geom_smooth()` using formula 'y ~ x'
## `summarise()` ungrouping output (override with `.groups` argument)
## `geom_smooth()` using formula 'y ~ x'
## `summarise()` regrouping output by 'year' (override with `.groups` argument)
## `geom_smooth()` using formula 'y ~ x'