README.md

In sheila-NAA/Mastering-software-development: Cleaning Raw Data

buildingpackage

The goal of buildingpackage is to show information about history of earthquake around the world.

To do that, it provide a raw version of the NOAA Significant Earthquake DatabaseD.

Installation

You can install the released version of buildingpackage from CRAN with:

install.packages("buildingpackage")'=

requireNamespace("DT", quietly = TRUE)
requireNamespace("lubridate", quietly = TRUE)
requireNamespace("ggplot2", quietly = TRUE)
library(devrcap)
    data("noaa")
DT::datatable(noaa)

Example

This is a basic example which shows you how to solve a common problem:

library(buildingpackage)
## basic example code

The first function implemented would be used to clean this database and prepare it for further analyses and visualizations.

More in details, the function eq_clean_data() produce a dataset with the following characteristics:

• A date column created by uniting the year, month, day and converting it to the Date class

• latitude and longitude columns converted to numeric class

• use the funciton eq_location_clean() (from the devrcap package too) to clean the location_name column by stripping out the country name (including the colon) and converting names to title case (as opposed to all caps).

• set all the column names to lowercase

data_cleaned <- devrcap::eq_clean_data(noaa) 
DT::datatable(data_cleaned)

Using the ggplot2 geom geom_timeline() provided by devrcap, we can use the cleaned data to plot time lines of earthquakes both overall and by group (e.g., country).

Moreover, using geom_timeline_label() we can add information about the earthquakes, e.g. the location. Due to the possible huge ammount of information that could be displayed, an option n_max can be used to limit the ammount of information to show. If the size option is also provided to ggplot, the n_max option will show the n_max largest earthquakes (otherwise it will be simply sample n_max earthquakes at random to show the information about the location)

```{r, fig.cap = "Time lines of earthquakes in Greece, Italy and Portugal, from 1900 to date. For each earthquake, the point size is proportional with intensity, colour gradient is proportional with total number of death."} noaa %>% eq_clean_data() %>% dplyr::filter( country %in% c("ITALY", "GREECE", "PORTUGAL"), lubridate::year(date) >= 1900 ) %>% ggplot2::ggplot(ggplot2::aes( x = date, y = country, size = eq_primary, colour = log(total_deaths), label = location_name )) + geom_timeline() + geom_timeline_label(n_max = 3) + ggplot2::theme(legend.position = "bottom")

Using the funciton `eq_map()` we can also show an interactive map of earthquakes, and with the functionality added by the function `eq_create_label()` we can also show (interactively) information (when
present) about location, magnitude and total death of each earthquakes.

```{r}
noaa %>%
    eq_clean_data %>%
    dplyr::filter(
        country == "MEXICO",
        lubridate::year(date) >= 2000
    ) %>%
    dplyr::mutate(popup_text = eq_create_label(.)) %>%
    eq_map("popup_text")

sheila-NAA/Mastering-software-development documentation built on Dec. 23, 2021, 1:22 a.m.