Bigfoot Final Project
Reine Albite
2022-11-28
library(tidyverse)## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.6 v dplyr 1.0.7
## v tidyr 1.1.4 v stringr 1.4.0
## v readr 2.1.1 v forcats 0.5.1## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(ggplot2)
library(dplyr)
library(sf)## Warning: package 'sf' was built under R version 4.1.3## Linking to GEOS 3.10.2, GDAL 3.4.1, PROJ 7.2.1; sf_use_s2() is TRUElibrary(ggthemes)## Warning: package 'ggthemes' was built under R version 4.1.3library(wordcloud)## Warning: package 'wordcloud' was built under R version 4.1.3## Loading required package: RColorBrewerlibrary(RColorBrewer)#Downloading the Data from Tidy Tuesday
tuesdata <- tidytuesdayR::tt_load('2022-09-13')## --- Compiling #TidyTuesday Information for 2022-09-13 ----## --- There is 1 file available ---## --- Starting Download ---##
## Downloading file 1 of 1: `bigfoot.csv`## --- Download complete ---tuesdata <- tidytuesdayR::tt_load(2022, week = 37)## --- Compiling #TidyTuesday Information for 2022-09-13 ----## --- There is 1 file available ---## --- Starting Download ---##
## Downloading file 1 of 1: `bigfoot.csv`## --- Download complete ---bigfoot <- tuesdata$bigfoot
bigfoot <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-09-13/bigfoot.csv')## Rows: 5021 Columns: 28## -- Column specification --------------------------------------------------------
## Delimiter: ","
## chr (10): observed, location_details, county, state, season, title, classif...
## dbl (17): latitude, longitude, number, temperature_high, temperature_mid, t...
## date (1): date##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.#Cleaning the data
bigfoot2c <- na.omit(bigfoot)
bigfoot2c[!duplicated(bigfoot2c), ]summary(bigfoot2c)## observed location_details county state
## Length:722 Length:722 Length:722 Length:722
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## season title latitude longitude
## Length:722 Length:722 Min. :25.14 Min. :-149.77
## Class :character Class :character 1st Qu.:36.89 1st Qu.:-111.76
## Mode :character Mode :character Median :40.42 Median : -87.25
## Mean :40.07 Mean : -94.35
## 3rd Qu.:44.70 3rd Qu.: -81.49
## Max. :64.89 Max. : -68.23
## date number classification geohash
## Min. :1961-09-01 Min. : 77 Length:722 Length:722
## 1st Qu.:2002-10-02 1st Qu.: 9333 Class :character Class :character
## Median :2007-10-22 Median :25792 Mode :character Mode :character
## Mean :2006-10-12 Mean :30196
## 3rd Qu.:2014-11-13 3rd Qu.:49880
## Max. :2021-11-27 Max. :71997
## temperature_high temperature_mid temperature_low dew_point
## Min. : 9.80 Min. : 8.595 Min. : 0.09 Min. :-1.83
## 1st Qu.:49.60 1st Qu.:43.731 1st Qu.:36.26 1st Qu.:38.01
## Median :62.55 Median :55.585 Median :48.23 Median :47.91
## Mean :62.84 Mean :55.566 Mean :48.29 Mean :48.62
## 3rd Qu.:78.22 3rd Qu.:69.285 3rd Qu.:61.36 3rd Qu.:62.72
## Max. :98.15 Max. :85.950 Max. :84.34 Max. :77.40
## humidity cloud_cover moon_phase precip_intensity
## Min. :0.0800 Min. :0.0000 Min. :0.0100 Min. :0.00010
## 1st Qu.:0.7400 1st Qu.:0.4100 1st Qu.:0.2500 1st Qu.:0.00070
## Median :0.8100 Median :0.7000 Median :0.5200 Median :0.00305
## Mean :0.8003 Mean :0.6419 Mean :0.4987 Mean :0.01036
## 3rd Qu.:0.8800 3rd Qu.:0.9100 3rd Qu.:0.7600 3rd Qu.:0.01080
## Max. :1.0000 Max. :1.0000 Max. :0.9900 Max. :0.20580
## precip_probability precip_type pressure summary
## Min. :0.010 Length:722 Min. : 980.3 Length:722
## 1st Qu.:0.500 Class :character 1st Qu.:1011.7 Class :character
## Median :0.950 Mode :character Median :1015.1 Mode :character
## Mean :0.744 Mean :1015.2
## 3rd Qu.:1.000 3rd Qu.:1019.2
## Max. :1.000 Max. :1038.0
## uv_index visibility wind_bearing wind_speed
## Min. : 0.000 Min. : 0.740 Min. : 0.0 Min. : 0.100
## 1st Qu.: 2.000 1st Qu.: 6.822 1st Qu.:134.0 1st Qu.: 1.502
## Median : 4.000 Median : 8.940 Median :204.5 Median : 3.420
## Mean : 4.731 Mean : 8.013 Mean :199.1 Mean : 4.024
## 3rd Qu.: 7.000 3rd Qu.: 9.845 3rd Qu.:260.0 3rd Qu.: 5.630
## Max. :12.000 Max. :10.000 Max. :359.0 Max. :23.940bigfoot2c <- bigfoot2c %>%
mutate(year = as.numeric(format(date,'%Y')))
view(bigfoot2c)#How many bigfoot sightings has there been over the years?
bigfoot2c %>%
ggplot(aes(year)) +
geom_histogram(color = "aquamarine4", fill = "aquamarine") +
labs(x="year of sightings",
y = "# of sightings",
title = "Amount of bigfoot sightings")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#Map of sightings in U.S
bigfoot2c %>%
filter(state != "Alaska") %>%
ggplot(aes(longitude,latitude, color = season)) +
geom_point() +
borders("state") +
coord_map() +
labs(title = "Bigfoot Sightings in the U.S")
#So what states was bigfoot seen?
bigfoot2c %>%
count(state, sort = TRUE)WA <- bigfoot2c %>%
filter(state == "Washington") %>%
select(county,number,season,temperature_mid)
WA#Where in WA was bigfoot seen?
attempt <- WA %>%
count(county, sort = TRUE)
ggplot(attempt, aes(county,n)) +
geom_point() +
theme_minimal(base_size = 10)+
theme(axis.text.x = element_text(size = 8, angle = 90)) +
labs(title = "WA county sightings", x="counties",y = "# of sightings")
#Which seasons did bigfoot appear?
d <- bigfoot2c %>%
mutate(season = na_if(season, "Unknown")) %>%
filter(!is.na(season)) %>%
ggplot(aes(year, fill = season)) +
geom_bar() +
facet_wrap(~season) +
labs(x="Year",
y = "# of sightings",
title = "Seasonal Sightings") +
theme(axis.text.x = element_text(size = 9, angle = 50))
d
ggplot(bigfoot2c, aes(x = 1, y = season, fill = season)) +
geom_col() +
coord_polar(theta='y') +
theme_void() +
ggtitle("Seasons of bigfoot sightings")
#Most common words to describe bigfoot observations?
wordcloud(words = bigfoot2c$observed, min.freq = 1, max.words=1000, colors=brewer.pal(8, "BrBG"))## Loading required namespace: tm## Warning in tm_map.SimpleCorpus(corpus, tm::removePunctuation): transformation
## drops documents## Warning in tm_map.SimpleCorpus(corpus, function(x) tm::removeWords(x,
## tm::stopwords())): transformation drops documents## Warning in wordcloud(words = bigfoot2c$observed, min.freq = 1, max.words =
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