ggfertilizer

Retrieve, Summarize and Visualize the Fertilizer Data in USA

Provides a user-friendly API to further dig in County-Level Fertilizer data in USA, provided by USGS.

Installation

This package can be installed via github using devtools.

# install.package("devtools")   #In case you have not installed it.
devtools::install_github("wenlong-liu/ggfertilizer")

Quick Start

Import data and libraries

require(ggfertilizer)
require(dplyr)
#> Warning: package 'dplyr' was built under R version 3.5.1
require(ggplot2)
data("us_fertilizer_county")

Retrieve fertilizer data

Year <-  2008
Nutrient <- "N"
Input_Type <- "fertilizer"

# retrieve data.
plot_data <- get_data(data = us_fertilizer_county, years = Year, nutrient = Nutrient, 
                      input_type = Input_Type,  combine_state_county = TRUE)
head(plot_data)
#> # A tibble: 6 x 12
#>   FIPS  State County       ALAND  AWATER INTPTLAT INTPTLONG Quantity Year 
#>   <chr> <chr> <chr>        <dbl>   <dbl>    <dbl>     <dbl>    <dbl> <chr>
#> 1 01001 AL    Autauga,…   1.54e9  2.58e7     32.5     -86.6   783984 2008 
#> 2 01003 AL    Baldwin,…   4.12e9  1.13e9     30.7     -87.7  4948455 2008 
#> 3 01005 AL    Barbour,…   2.29e9  5.09e7     31.9     -85.4  1171588 2008 
#> 4 01007 AL    Bibb, AL    1.61e9  9.29e6     33.0     -87.1   141669 2008 
#> 5 01009 AL    Blount, …   1.67e9  1.52e7     34.0     -86.6  1206109 2008 
#> 6 01011 AL    Bullock,…   1.61e9  6.06e6     32.1     -85.7   629577 2008 
#> # ... with 3 more variables: Nutrient <chr>, Farm.Type <chr>,
#> #   Input.Type <chr>

Summarize and plot data.

Example 1: Find out the top 10 counties with most nitrogen appliation in 2008.

# plot the top 10 nitrogen application in year 2008.
plot <- plot_data %>% 
  top_n(10, Quantity) %>%
  ggplot(aes(x=reorder(County, Quantity), Quantity, fill = Quantity))+
  scale_fill_gradient(low = "yellow", high = "brown")+
  geom_col()+
  ggtitle(paste("Top 10 counties with most N fertilizer application in the year of", Year)) + 
  scale_y_continuous(name = "Nitrogen from commecial fertilization (kg)")+
  scale_x_discrete(name = "Counties")+
  coord_flip()+
  theme_bw()
plot

Examples 2: Visualize the fertilizer data in US maps.

Year = 2001
Nutrient = "N"
Farm_Type = "farm"
Input_Type = "fertilizer"
level  = "county" 

# draw the map
us_plot <- map_us_fertilizer(data = us_fertilizer_county, Year = Year, Nutrient = Nutrient,
                             Farm_Type = Farm_Type, Input_Type = Input_Type, 
                             viridis_palette = "inferno", level = level) 
us_plot

As the maps are actually ggplot2 objects, all the common API for ggplot2 can be used here. We can also add a title for the map to make it more informative.

us_plot +
  ggtitle(paste(Nutrient,  " from ", Input_Type, " input to ", Farm_Type, " in the year of ",Year,
                     " at ", level, " level",sep = ""))

For more details about mapping fertilizer data, please see this vignettes of plotting us maps of fertilizer.

Example 3: Visualize the fertilizer data for certain states or counties.

Year = 2011
Nutrient = "P"
Farm_Type = "nonfarm"
Input_Type = "fertilizer"
level  = "county" 
State = c("NC", "SC")

# draw the map
state_plot <- map_us_fertilizer(data = us_fertilizer_county, Year = Year, Nutrient = Nutrient,
                             Farm_Type = Farm_Type, Input_Type = Input_Type, State = State,
                             viridis_palette = "inferno", level = level) +
              ggtitle(paste(Nutrient,  " from ", Input_Type, " input to ", Farm_Type, " in the year of ",Year,
                       " at ", level, " level for Carolinas",sep = ""))
state_plot

For more details about mapping fertilizer data, please see this vignettes of plotting state maps

Generate summaries plots.

(Under development on July 10, 2018)

Comments and Questions

If you have any problems or questions, feel free to open an issue here.

Lisence

GPL

Code of conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.