Created
July 30, 2018 13:17
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Import messy hurricane data
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| library(tidyverse) | |
| library(xml2) | |
| url <- "http://www.aoml.noaa.gov/hrd/hurdat/hurdat2-nepac.html" | |
| # Column names ------------------------------------------------------------ | |
| # From: http://www.aoml.noaa.gov/hrd/hurdat/newhurdat-format.pdf | |
| # for the data lines | |
| wind_vars <- cross_df(list( | |
| y = c("NE", "SE", "SW", "NW"), | |
| x = c("34", "50", "64"))) %>% | |
| glue::glue_data("winds_{x}_{y}") | |
| col_names <- c("date", "time", | |
| "record_id", "status", "lat", "lon", | |
| "max_wind", "min_pressure", wind_vars, "empty" | |
| ) | |
| # Import ------------------------------------------------------------------ | |
| hurricanes <- read_html(url) %>% | |
| xml_find_first(".//pre") %>% | |
| xml_text() %>% | |
| read_csv(col_names = col_names, | |
| col_types = cols(record_id = col_character())) | |
| # Warnings correspond to header lines | |
| problems(hurricanes) | |
| # Pull apart header and data rows ----------------------------------------- | |
| # Find headers based on first two characters in first column (date) | |
| # specifiying basin | |
| hurricanes <- hurricanes %>% | |
| mutate( | |
| header = str_detect(date, "[A-Z]{2}"), | |
| id = cumsum(header) | |
| ) | |
| # Now for each hurricane add header info as columns to data | |
| hurricanes_tidy <- hurricanes %>% | |
| group_by(id) %>% | |
| mutate( | |
| cyclone_id = first(date), | |
| name = first(time), | |
| n_records = first(record_id) | |
| ) %>% | |
| slice(-1) %>% | |
| ungroup() | |
| # and fix up a few data types | |
| hurricanes_clean <- | |
| hurricanes_tidy %>% | |
| mutate( | |
| datetime = lubridate::ymd_hm(paste(date, time, sep = "T")), | |
| date = lubridate::date(datetime), | |
| time = hms::as.hms(datetime), | |
| lat = parse_number(lat), | |
| lon = parse_number(lon) | |
| ) | |
| # some quick checks ------------------------------------------------------- | |
| # number of records matches that reported | |
| hurricanes_clean %>% | |
| group_by(cyclone_id) %>% | |
| summarise(n = n(), | |
| n_records = first(n_records), | |
| match = n == n_records) %>% | |
| summarise(all(match)) | |
| # Quick messy plot | |
| hurricanes_clean %>% | |
| ggplot(aes(lon, lat)) + | |
| geom_path(aes(group = cyclone_id)) |
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