JosiahParry

sq <- ggplot((na.omit(threats)), aes(factor(soil_quality)))+ geom_bar() + facet_grid(~Gender) + aes(fill = Gender)
wq <- ggplot((na.omit(threats)), aes(factor(waterquality))) + geom_bar()+ facet_grid(~Gender) + aes(fill = Gender)
wl <- ggplot((na.omit(threats)), aes(factor(wildlife))) + geom_bar()+ facet_grid(~Gender) + aes(fill = Gender)
rec <- ggplot((na.omit(threats)), aes(factor(recreation))) + geom_bar() + facet_grid(~Gender) + aes(fill = Gender)
scen <- ggplot((na.omit(threats)), aes(factor(scenic))) + geom_bar() + facet_grid(~Gender) + aes(fill = Gender)
tour <- ggplot((na.omit(threats)), aes(factor(tourism))) + geom_bar() + facet_grid(~Gender) + aes(fill = Gender)
biz <- ggplot((na.omit(threats)), aes(factor(business))) + geom_bar() + facet_grid(~Gender) + aes(fill = Gender)
rur <- ggplot((na.omit(threats)), aes(factor(rural))) + geom_bar() + facet_grid(~Gender) + aes(fill = Gender) 

JosiahParry

# Create a tibble with the artist's name & another with the album title

kdot_albums <- tibble(
  artist = "Kendrick Lamar",
  album = c("Section 80", "DAMN."))
  
# Iterate through the albums and artists using a map call
album_lyrics <- kdot_albums %>%
  mutate(tracks = map2(artist, album, genius_album))

JosiahParry

library(genius)
library(tidytext)
library(tidyverse)


# get lyrics for album
since_96 <- genius_album("ALIX", "since 96")

# calculate self similarity by group (thank you dplyr v 0.8!!!)
self_sim_96 <- since_96 %>% 

JosiahParry

# create function for getting song features
track_audio_features <- function(artist, title, type = "track") {
  search_results <- search_spotify(paste(artist, title), type = type)
  track_audio_feats <- get_track_audio_features(search_results$id[[1]]) %>%
    dplyr::select(-id, -uri, -track_href, -analysis_url)
  
  return(track_audio_feats)
}

# create a version of this function which can handle errors

JosiahParry

library(trendyy)
library(tidyverse)

candidates <- c("joe biden", "kamala harris", "elizabeth warren", "pete buttigieg", "cory booker")

candidate_trends <- trendy(candidates, from = "2019-06-15", to = Sys.Date())

get_interest(candidate_trends) %>% 
  filter(date >= "2019-06-25") %>% 
  ggplot(aes(date, hits, color = keyword)) +

JosiahParry

library(httr)
library(jsonlite)
res <- GET("http://api.themoviedb.org/3/discover/movie?release_date.gte=2017-12-01&release_date.lte=2017-12-31&api_key=606aaffd7ca10f0b80804a1f0674e4e1&page=1") %>% 
  content("text") %>% 
  fromJSON()



int0_to_na <- function(x) {

JosiahParry

---
title: "∑ { _my parts_ }"
output: github_document
---

```{r message=FALSE, warning=FALSE}
library(tidyverse)

terrorists <- googlesheets::gs_url("https://docs.google.com/spreadsheets/d/1LYQakIwGosibDHJKJqZgjM39qpSlp_gFG29zJ6paDAI/edit#gid=956062857") %>% 
  googlesheets::gs_read()

JosiahParry

library(sqldf)
library(tidyverse)


polls <- read_csv("https://raw.githubusercontent.com/JosiahParry/r-4-campaigns/master/data/polls.csv")

sqldf("select candidate, count(*) as n
      from polls 
      where points > 20 
      group by candidate 

JosiahParry

track_audio_features <- possibly(.f = {
  function(artist, title, type = "track") {
    search_results <- search_spotify(paste(artist, title), type = type)
    track_audio_feats <- get_track_audio_features(search_results$id[[1]]) %>%
      dplyr::select(-id, -uri, -track_href, -analysis_url)
    
    return(track_audio_feats)
}}, otherwise = tibble())

JosiahParry

library(tidyverse)

dice_words <- read_tsv("https://www.eff.org/files/2016/07/18/eff_large_wordlist.txt",
                       col_names = c("dice_id", "dice_word"), col_types = "cc")


diceware <- function(n_words) {
  map_dfr(1:n_words, ~tibble(dice_id = paste(sample(1:6, 5, replace = TRUE), collapse = ""))) %>% 
    left_join(dice_words) 
}