[We'd like to thank Phish nerd extraordinaire, Maya Gans (@WindoraBug on .net, @mayacelium on Twitter), for writing this post and sharing the phishr library that she wrote with Sam Levin (@levisc8 on .net, @SamLevin5 on Twitter) with the community - ed.]

When I tell people I meet outside of the scene that I’m a Phish fan it’s always met with a certain look - you know the one. But this always makes me laugh because one of the reasons I love Phish so much is how they provide one of the richest data sets to adoring fans. I love when folks who say they hate math or statistics end up rattling off their most seen songs, largest song gaps they need to close, or provide feedback on graphs I put up on Twitter.

Phish fans love data, and for that reason Sam Levin and I created the R package phishr. You can request an API Key here and our packages have a handful of functions that help do the heavy lifting.

# load the libraries
library(phishr)
library(purrr)
library(dplyr)
library(ggplot2)

We can use the setlist function which takes on two arguments - your API key [I’ve saved mine to a string called my_apikey] and the show date you’d like the setlist of.

Looking at the most recent setlist:

pn_get_setlist(my_apikey, "2020-02-23")

## Set Song Segue ## 1 Set 1 Crowd Control , ## 2 Set 1 Farmhouse , ## 3 Set 1 Breath and Burning , ## 4 Set 1 Divided Sky , ## 5 Set 1 Meat , ## 6 Set 1 Everything's Right , ## 7 Set 1 The Squirming Coil , ## 8 Set 1 Wingsuit , ## 9 Set 1 David Bowie ## 10 Set 2 Simple > ## 11 Set 2 Golden Age > ## 12 Set 2 Fuego > ## 13 Set 2 Undermind -> ## 14 Set 2 Back on the Train > ## 15 Set 2 Passing Through ## 16 Encore Rise/Come Together > ## 17 Encore The Horse > ## 18 Encore Silent in the Morning , ## 19 Encore Fee , ## 20 Encore Funky Bitch , ## 21 Encore More

If you want to select multiple shows you can use a map function to apply the setlist function to each show date:

First we’ll create a vector of the show dates we want setlists for Then we can map the setlist function on each of the show dates Then we need to add a column that corresponds to the Date of each show

Mexico <- c("2020-02-20", "2020-02-21", "2020-02-22", "2020-02-23")
setlists <- map(Mexico, ~pn_get_setlist(apikey = my_apikey, .x))

Phexico <- map2_dfr(setlists, Mexico, ~mutate(.x, Date = .y))

Phexico

## Set Song Segue Date ## 1 Set 1 Torn and Frayed > 2020-02-20 ## 2 Set 1 Ghost > 2020-02-20 ## 3 Set 1 Free > 2020-02-20 ## 4 Set 1 Shipwreck -> 2020-02-20 ## 5 Set 1 Free , 2020-02-20 ## 6 Set 1 Shake Your Coconuts , 2020-02-20 ## 7 Set 1 Victim , 2020-02-20 ## 8 Set 1 The Moma Dance > 2020-02-20 ## 9 Set 1 Gotta Jibboo , 2020-02-20 ## 10 Set 1 Shade , 2020-02-20 ## 11 Set 1 The Landlady > 2020-02-20 ## 12 Set 1 Destiny Unbound , 2020-02-20 ## 13 Set 1 Steam > 2020-02-20 ## 14 Set 1 Crosseyed and Painless > 2020-02-20 ## 15 Set 1 Run Like an Antelope > 2020-02-20 ## 16 Set 1 Cavern > 2020-02-20 ## 17 Set 1 Beneath a Sea of Stars Part 1 > 2020-02-20 ## 18 Set 1 Say It To Me S.A.N.T.O.S. 2020-02-20 ## 19 Encore You Enjoy Myself 2020-02-20 ## 20 Set 1 Turtle in the Clouds , 2020-02-21 ## 21 Set 1 Shafty -> 2020-02-21 ## 22 Set 1 Plasma -> 2020-02-21 ## 23 Set 1 Shafty -> 2020-02-21 ## 24 Set 1 Plasma > 2020-02-21 ## 25 Set 1 The Lizards , 2020-02-21 ## 26 Set 1 Bathtub Gin -> 2020-02-21 ## 27 Set 1 Shafty -> 2020-02-21 ## 28 Set 1 Bathtub Gin > 2020-02-21 ## 29 Set 1 Blaze On , 2020-02-21 ## 30 Set 1 Sea and Sand , 2020-02-21 ## 31 Set 1 Possum 2020-02-21 ## 32 Set 2 Sigma Oasis > 2020-02-21 ## 33 Set 2 Also Sprach Zarathustra > 2020-02-21 ## 34 Set 2 Drift While You're Sleeping , 2020-02-21 ## 35 Set 2 Lifeboy , 2020-02-21 ## 36 Set 2 I Always Wanted It This Way -> 2020-02-21 ## 37 Set 2 No Men In No Man's Land -> 2020-02-21 ## 38 Set 2 Piper > 2020-02-21 ## 39 Set 2 Good Times Bad Times 2020-02-21 ## 40 Encore Sand -> 2020-02-21 ## 41 Encore Weekapaug Groove -> 2020-02-21 ## 42 Encore Shafty 2020-02-21 ## 43 Set 1 Willin' , 2020-02-22 ## 44 Set 1 Tube , 2020-02-22 ## 45 Set 1 Evening Song , 2020-02-22 ## 46 Set 1 Set Your Soul Free , 2020-02-22 ## 47 Set 1 You Sexy Thing > 2020-02-22 ## 48 Set 1 46 Days , 2020-02-22 ## 49 Set 1 Waste > 2020-02-22 ## 50 Set 1 Your Pet Cat , 2020-02-22 ## 51 Set 1 Tweezer > 2020-02-22 ## 52 Set 1 Manteca > 2020-02-22 ## 53 Set 1 Makisupa Policeman > 2020-02-22 ## 54 Set 1 Twist 2020-02-22 ## 55 Set 2 Energy > 2020-02-22 ## 56 Set 2 Soul Planet > 2020-02-22 ## 57 Set 2 Waves > 2020-02-22 ## 58 Set 2 Carini > 2020-02-22 ## 59 Set 2 Chalk Dust Torture -> 2020-02-22 ## 60 Set 2 Have Mercy > 2020-02-22 ## 61 Set 2 A Life Beyond The Dream , 2020-02-22 ## 62 Set 2 Harry Hood 2020-02-22 ## 63 Encore Sweet Jane > 2020-02-22 ## 64 Encore Tweezer Reprise 2020-02-22 ## 65 Set 1 Crowd Control , 2020-02-23 ## 66 Set 1 Farmhouse , 2020-02-23 ## 67 Set 1 Breath and Burning , 2020-02-23 ## 68 Set 1 Divided Sky , 2020-02-23 ## 69 Set 1 Meat , 2020-02-23 ## 70 Set 1 Everything's Right , 2020-02-23 ## 71 Set 1 The Squirming Coil , 2020-02-23 ## 72 Set 1 Wingsuit , 2020-02-23 ## 73 Set 1 David Bowie 2020-02-23 ## 74 Set 2 Simple > 2020-02-23 ## 75 Set 2 Golden Age > 2020-02-23 ## 76 Set 2 Fuego > 2020-02-23 ## 77 Set 2 Undermind -> 2020-02-23 ## 78 Set 2 Back on the Train > 2020-02-23 ## 79 Set 2 Passing Through 2020-02-23 ## 80 Encore Rise/Come Together > 2020-02-23 ## 81 Encore The Horse > 2020-02-23 ## 82 Encore Silent in the Morning , 2020-02-23 ## 83 Encore Fee , 2020-02-23 ## 84 Encore Funky Bitch , 2020-02-23 ## 85 Encore More 2020-02-23

And now we have data to look at some numbers! How about number of songs per set per show?

(
song_counts <- Phexico %>%
mutate(Set = factor(Set, levels = c("Set 1", "Set 2", "Encore"))) %>%
group_by(Set, Date) %>%
count()
)

## # A tibble: 11 x 3 ## # Groups: Set, Date [11] ## Set Date n ## ## 1 Set 1 2020-02-20 18 ## 2 Set 1 2020-02-21 12 ## 3 Set 1 2020-02-22 12 ## 4 Set 1 2020-02-23 9 ## 5 Set 2 2020-02-21 8 ## 6 Set 2 2020-02-22 8 ## 7 Set 2 2020-02-23 6 ## 8 Encore 2020-02-20 1 ## 9 Encore 2020-02-21 3 ## 10 Encore 2020-02-22 2 ## 11 Encore 2020-02-23 6

And we can visualize that:

ggplot(song_counts, aes(x = Set, y = n, fill = Set)) +
geom_bar(stat = "identity") +
facet_wrap(.~ Date) +
theme_bw()

We can also use the function pn_get_show_notes for each show and scrape this for text data or teases

notes <- map(Mexico, ~pn_get_show_notes(apikey = my_apikey, .x)) %>% unlist()
names(notes) <- Mexico

# show the first show's note
notes[1]

## 2020-02-20 ## "This show was webcast via LivePhish and featured multiple bustouts: Torn and Frayed was last played on July 7, 2012 (285 shows), Shipwreck was last played on October 31, 2014 (189 shows), and Shake Your Coconuts was played on July 21, 2017 (100 shows). The return to Free contained Rescue Squad and Shipwreck quotes. The lyrics in Shake Your Coconuts were changed to "It's Phish in Mexico time." Trey teased Walk This Way in You Enjoy Myself.via phish.net"

Lastly we can look at ratings:

(
ratings <- map(Mexico, ~pn_get_show_rating(apikey = my_apikey, .x)) %>% unlist()
)

## [1] 3.4591 3.8567 4.0376 3.5541

Is number of songs per show a good predictor of rating?

# group data by number of songs
counts_per_show <- Phexico %>%
group_by(Date) %>%
count()

# add the ratings to the data
counts_per_show$rating <- ratings

counts_per_show

## # A tibble: 4 x 3 ## # Groups: Date [4] ## Date n rating ## ## 1 2020-02-20 19 3.46 ## 2 2020-02-21 23 3.86 ## 3 2020-02-22 22 4.04 ## 4 2020-02-23 21 3.55

Run a simple linear model

model <- lm(rating ~ n, data = counts_per_show)
x <- summary(model)
pf(x$fstatistic[1L], df1 = x$fstatistic[2L], df2 = x$fstatistic[3L], lower.tail = FALSE)

## [1] 0.1938811

Nope. Not significant at all. BUT! I hope this is a fun introduction to a package that inspires you to look at this rich data set you love, test your hypotheses, and create visualizations! Feel free to reach out to me or Sam on our GitHub account.

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