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[](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") ```