[](https://travis-ci.org/atibot/eqplot)
# Package "eqplot"
This package will provide tools to visualize the earthquake dataset obtained from the U.S. National Oceanographic and Atmospheric Administration (NOAA) on significant earthquakes around the world. This dataset contains information about 5,933 earthquakes over an approximately 4,000 year time span.
## Installation
You can install eqplot from github with:
```{r gh-installation, eval = FALSE}
# install.packages("devtools")
devtools::install_github("atibot/eqplot", build_vignettes = TRUE)
```
## Examples
These are basic examples which show you how to solve common problems.
### Timeline plot
```{r example_timeline, eval = FALSE}
## basic example code
library(dplyr)
library(lubridate)
data("raw_df")
test_df <-
raw_df %>% eq_clean_data() %>%
dplyr::filter(COUNTRY == "TURKEY" | COUNTRY == "JAPAN") %>%
dplyr::filter(DATE >= eq_date("2000-01-01") & DATE <= eq_date("2017-01-01"))
# plot timeline
ggtimeline <- ggplot2::ggplot(test_df)
ggtimeline2 <- ggtimeline + geom_timeline(
ggplot2::aes(
x = DATE,
y = COUNTRY,
size = EQ_PRIMARY,
fill = TOTAL_DEATHS
)
) +
eq_theme +
ggplot2::scale_size_continuous(name = "Richer scale value", breaks = c(0, 2, 4, 6, 8)) +
ggplot2::scale_fill_continuous(name = "# deaths") +
ggplot2::labs(title = "Earthquakes")
# plot labels
ggtimeline3 <- ggtimeline2 + geom_timeline_label(ggplot2::aes(
x = DATE,
y = COUNTRY,
mag = EQ_PRIMARY,
label = LOCATION_NAME
),
n_max = 5)
#draw plot
ggtimeline3
```
### Map plot with Date
```{r example_map1, eval = FALSE}
data("raw_df")
raw_df %>% eq_clean_data() %>%
dplyr::filter(COUNTRY == "MEXICO" & lubridate::year(DATE) >= 2000) %>%
eq_map(annot_col = "DATE")
```
### Map plot with Date, Location, Magnitude and Deaths
```{r example_map2, , eval = FALSE}
data("raw_df")
raw_df %>% eq_clean_data() %>%
dplyr::filter(COUNTRY == "MEXICO" & lubridate::year(DATE) >= 2000) %>%
dplyr::mutate(popup_text = eq_create_label(.)) %>%
eq_map(annot_col = "popup_text")
```
### Map plot with Cluster options
```{r example_map3, , eval = FALSE}
data("raw_df")
raw_df %>% eq_clean_data() %>%
dplyr::mutate(popup_text = eq_create_label(.)) %>%
eq_map(annot_col = "popup_text", cluster = TRUE)
```
## Vignette
Once the package is installed, view the vignette for more details.
```{r vignette, eval= FALSE}
vignette(topic = "eqplot", package = "eqplot")
```
