README.md
In maianhdang/noaa.visualise: NOAA Earthquakes Processing and Visualising

Visualize NOAA Significant Earthquakes dataset

This is noaa.visualise package, working with the NOAA Significant Earthquakes dataset to support the process of visualising and gaining information.

The packages includes the below groups:

Group | Functions ----------------------| ---------------------------- Cleaning the raw data | eq_clean_data(), eq_location_clean(), eq_country_filter() Visualisation tools | geom_timeline(), geom_timeline_lable(), stat_timeline(), theme_timeline() Mapping tools | eq_map(), eq_create_label()

You can install noaa.visualise from github with:

```{r gh-installation, eval = FALSE}

install.packages("devtools")

devtools::install_github("maianhdang/noaa.visualise")

## Included dataset


The [NOAA Significant Earhquake Dataset](https://www.ngdc.noaa.gov/nndc/struts/form?t=101650&s=1&d=1) contains the information of 5,933 earthquakes over the period of 4,000 years.

**Cite:** National Geophysical Data Center / World Data Service (NGDC/WDS): Significant Earthquake Database. National Geophysical Data Center, NOAA. doi:10.7289/V5TD9V7K

## Further information about usage
The vignettes is included in the package. Call the vignettes by:
  `vignette('introduction', package = 'noaa.visualise')`

## Examples

### Visualize earthquakes by timeline

```{r visual_1}
data("raw_data")
data <- noaa.visualise::eq_clean_data(raw_data)
data <- noaa.visualise::eq_location_clean(data) ## to create the text annotation
input_data <- noaa.visualise::eq_country_filter(data, countries = c("MEXICO", "IRAN"),
                                            xmin = as.Date("1000-01-01"),
                                            xmax = as.Date("2010-01-01"))

ggplot2::ggplot(input_data, ggplot2::aes (x = date, y = COUNTRY, color = as.numeric(DEATHS), 
size = as.numeric(EQ_PRIMARY))) +

## geom_timeline  
noaa.visualise::geom_timeline(ggplot2::aes(xmin = as.Date("1900-01-01"), 
xmax =  as.Date("1925-01-01"))) +
ggplot2::labs(size = "Richter Scale Values", color = "Number of Deaths" )+

## geom_timeline_label  
noaa.visualise::geom_timeline_label(ggplot2::aes(label = LOCATION_NAME, 
                          xmin = as.Date("1900-01-01"), xmax = as.Date("1925-01-01")), 
                          n_max = 5) + 

noaa.visualise::theme_timeline()

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```{r map_1} library(magrittr) data("raw_data") data <- noaa.visualise::eq_clean_data(raw_data) input_data <- dplyr::filter(data, COUNTRY == "MEXICO" & lubridate::year(date) >= 2000)%>% dplyr::mutate(popup_text = noaa.visualise::eq_create_label(.)) ## create popup_text

noaa.visualise::eq_map(input_data, annot_col = "popup_text") ## annot_col set as popup_text

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