Merge pull request #195 from tyluRp/master
Change scrape.R in police-deaths
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.gitignore
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2
.gitignore
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@@ -1,3 +1,3 @@
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.DS_Store
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aws.json
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.Rhistory
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.Rhistory
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@@ -1,41 +1,27 @@
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#-------------------------------------------------------------------------------
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# Dallas shooting scraping
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#-------------------------------------------------------------------------------
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library(dplyr)
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library(tidyverse)
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library(rvest)
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library(readr)
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library(tidyr)
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library(lubridate)
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library(stringr)
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library(ggplot2)
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yearly_url <- 'https://www.odmp.org/search/year/'
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years <- seq(1791, 2016)
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all_data <- data.frame()
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# Scrape data
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df <- paste0("https://www.odmp.org/search/year/", seq(1791, 2016)) %>%
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as_tibble() %>%
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set_names("url") %>%
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mutate(
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data = map(url, read_html),
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nodes = map(data, html_nodes, '[class="officer-short-details"]'),
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text = map(nodes, html_text),
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clean_text = map(text, str_trim),
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clean_text = map(clean_text, str_replace_all, "\n", " separator"),
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clean_data = map(clean_text, as.data.frame),
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clean_data = map(clean_data, set_names, "string"),
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clean_data = map(clean_data, separate, string, c("person", "dept", "eow", "cause"), "separator")
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) %>%
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select(clean_data) %>%
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unnest() %>%
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mutate_all(str_squish)
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for (year in years){
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new_url <- paste0(yearly_url, year)
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selector_yearly <- 'p , p a'
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raw_data <- read_html(new_url) %>%
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html_nodes(selector_yearly) %>%
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html_text() %>%
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as.data.frame()
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names(raw_data) <- c("incident")
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clean_data <- raw_data %>%
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separate(incident, sep = '\n\t\t\t\t\t\t\t\t\t',
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into = c("person", "dept","eow", "cause")) %>%
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filter(!is.na(dept))
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all_data <- rbind(all_data, clean_data)
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}
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write_csv(all_data, "all_data_fallen_officers.csv")
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# Write to CSV
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write_csv(df, "all_data_fallen_officers.csv")
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