Tidyverse Assignment - Purrr and Forcats and Vignette
Cameron Smith and extended by Peter Fernandes
10/26/2020
Introduction
This vignette is focused on the purrr and forcats packages from the Tidyverse, and were chosen based on the simple logic that I am the least unfamiliar with them so it seemed like a good opportunity to change that.
Load packages
Loading the two packages directly, though you could also load the whole tidyverse package
library(purrr)
library(forcats)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionLoad the data
I used a dataset from Kaggle with information on Indian cuisine (link and info below. It is stored in Github for reproducibility.
https://www.kaggle.com/nehaprabhavalkar/indian-food-101 Version 2, Accessed 26 October 2020
file <- "https://raw.githubusercontent.com/cwestsmith/cuny-msds/master/datasets/indian_food.csv"
df <- read.csv(file, header = TRUE)
# Checking structure of new data frame. Lots of factors, which is good for this vignette
str(df)## 'data.frame': 255 obs. of 9 variables:
## $ name : chr "Balu shahi" "Boondi" "Gajar ka halwa" "Ghevar" ...
## $ ingredients : chr "Maida flour, yogurt, oil, sugar" "Gram flour, ghee, sugar" "Carrots, milk, sugar, ghee, cashews, raisins" "Flour, ghee, kewra, milk, clarified butter, sugar, almonds, pistachio, saffron, green cardamom" ...
## $ diet : chr "vegetarian" "vegetarian" "vegetarian" "vegetarian" ...
## $ prep_time : int 45 80 15 15 15 10 10 10 20 10 ...
## $ cook_time : int 25 30 60 30 40 50 50 20 30 40 ...
## $ flavor_profile: chr "sweet" "sweet" "sweet" "sweet" ...
## $ course : chr "dessert" "dessert" "dessert" "dessert" ...
## $ state : chr "West Bengal" "Rajasthan" "Punjab" "Rajasthan" ...
## $ region : chr "East" "West" "North" "West" ...Example 1: Forcats
Forcats is focused on making it easier to work with factors in R. One such function is fct_infreq(), which reorders a factor based on the frequency of values it has. In the example below I will use this function to reorder the flavor_profile variable based on the frequency of its levels in the dataset.
# View current structure of flavor_profile factor
levels(df$flavor_profile)## NULL# View summary of each flavor_profile based on # of entries
df %>% group_by(flavor_profile) %>% summarise(n())## `summarise()` ungrouping output (override with `.groups` argument)## # A tibble: 5 x 2
## flavor_profile `n()`
## <chr> <int>
## 1 -1 29
## 2 bitter 4
## 3 sour 1
## 4 spicy 133
## 5 sweet 88# Re-order the flavor_profile
df$flavor_profile <- fct_infreq(df$flavor_profile)
# Now view it again, which should match the order per the summary above
levels(df$flavor_profile)## [1] "spicy" "sweet" "-1" "bitter" "sour"Example 2: purrr
Purr is focused on making it easier to work with functions and vectors in R. One such function is pluck() which provides a flexible way to quickly extract an element. It has a sister function named chuck() which is similar except that it throws errors when something does not exist, rather than simply returning NULL.
# Create an example list
example_list <- as.list(df$ingredients)
# Pluck an element by index
pluck(example_list, 1)## [1] "Maida flour, yogurt, oil, sugar"# Searching for element that does not exist - pluck returns NULL
pluck(example_list, 100000)## NULL# But chuck returns an error
#chuck(example_list, 100000)Conclusion
In conclusion Forcats and Purr both include a wide array of useful functions which make it easier to work with various types of data in R.
From here onwards Extended by – Peter Fernandes
Capability 1 stringr::str_subset
Creating subset from the main set
# str_subset(string, pattern, negate = FALSE)
#flavor profile starting with - s
stringr::str_subset(df$flavor_profile, "^s")## [1] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [10] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [19] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [28] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [37] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [46] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [55] "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet" "sweet"
## [64] "sweet" "spicy" "spicy" "sweet" "spicy" "spicy" "spicy" "spicy" "spicy"
## [73] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy"
## [82] "spicy" "spicy" "sweet" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy"
## [91] "spicy" "spicy" "spicy" "sweet" "spicy" "spicy" "spicy" "spicy" "spicy"
## [100] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "spicy"
## [109] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "spicy"
## [118] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy"
## [127] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy"
## [136] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "spicy" "spicy"
## [145] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy"
## [154] "spicy" "spicy" "sweet" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy"
## [163] "spicy" "sweet" "spicy" "sweet" "spicy" "spicy" "sweet" "spicy" "sour"
## [172] "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "spicy" "spicy" "spicy"
## [181] "spicy" "spicy" "spicy" "spicy" "sweet" "spicy" "spicy" "spicy" "spicy"
## [190] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "sweet"
## [199] "sweet" "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "sweet" "spicy"
## [208] "spicy" "spicy" "spicy" "spicy" "spicy" "spicy" "sweet" "sweet" "spicy"
## [217] "spicy" "sweet" "sweet" "sweet" "sweet" "sweet"Capability 2 stringr::str_sort
Sort character vector
#str_sort(x, decreasing = FALSE, na_last = TRUE, locale = “en”,numeric = FALSE, …)
#decreasing= FALSE for Ascending order sort
stringr::str_sort(df$name, decreasing = FALSE)## [1] "Adhirasam" "Aloo gobi"
## [3] "Aloo matar" "Aloo methi"
## [5] "Aloo shimla mirch" "Aloo tikki"
## [7] "Alu Pitika" "Amti"
## [9] "Anarsa" "Ariselu"
## [11] "Attu" "Avial"
## [13] "Bajri no rotlo" "Balu shahi"
## [15] "Bandar laddu" "Basundi"
## [17] "Bebinca" "Beef Fry"
## [19] "Bengena Pitika" "Bhakri"
## [21] "Bhatura" "Bhindi masala"
## [23] "Bilahi Maas" "Biryani"
## [25] "Bisi bele bath" "Black rice"
## [27] "Bombil fry" "Boondi"
## [29] "Bora Sawul" "Brown Rice"
## [31] "Butter chicken" "Chak Hao Kheer"
## [33] "Chakali" "Cham cham"
## [35] "Chana masala" "Chapati"
## [37] "Cheera Doi" "Chevdo"
## [39] "Chhena jalebi" "Chhena kheeri"
## [41] "Chhena poda" "Chicken razala"
## [43] "Chicken Tikka" "Chicken Tikka masala"
## [45] "Chicken Varuval" "Chikki"
## [47] "Chingri Bhape" "Chingri malai curry"
## [49] "Chole bhature" "Chorafali"
## [51] "Churma Ladoo" "Coconut vadi"
## [53] "Copra paak" "Currivepillai sadam "
## [55] "Daal baati churma" "Daal Dhokli"
## [57] "Daal puri" "Dahi vada"
## [59] "Dal makhani " "Dal tadka"
## [61] "Dalithoy" "Dharwad pedha"
## [63] "Dhokla" "Dhondas"
## [65] "Doodhpak" "Dosa"
## [67] "Double ka meetha" "Dudhi halwa"
## [69] "Dum aloo" "Fara"
## [71] "Farsi Puri" "Gajar ka halwa"
## [73] "Galho" "Gatta curry"
## [75] "Gavvalu" "Gheela Pitha"
## [77] "Ghevar" "Ghooghra"
## [79] "Goja" "Gud papdi"
## [81] "Gulab jamun" "Halvasan"
## [83] "Hando Guri" "Handwo"
## [85] "Haq Maas" "Idiappam"
## [87] "Idli" "Imarti"
## [89] "Jalebi" "Jeera Aloo"
## [91] "Kaara kozhambu" "Kabiraji"
## [93] "Kachori" "Kadai paneer"
## [95] "Kadhi pakoda" "Kajjikaya"
## [97] "Kaju katli" "Kakinada khaja"
## [99] "Kalakand" "Kanji"
## [101] "Kansar" "Karela bharta"
## [103] "Keerai kootu" "Keerai masiyal"
## [105] "Keerai poriyal" "Keerai sadam"
## [107] "Keri no ras" "Khakhra"
## [109] "Khaman" "Khandvi"
## [111] "Khar" "Kheer"
## [113] "Kheer sagar" "Khichdi"
## [115] "Khichu" "Khorisa"
## [117] "Kofta" "Koldil Chicken"
## [119] "Koldil Duck" "Kolim Jawla"
## [121] "Kombdi vade" "Konir Dom"
## [123] "Kootu" "Kos kootu"
## [125] "Koshambri" "Koshimbir"
## [127] "Kothamali sadam" "Kulfi falooda"
## [129] "Kumol Sawul" "Kutchi dabeli"
## [131] "Kuzhakkattai" "Kuzhambu"
## [133] "Kuzhi paniyaram" "Laapsi"
## [135] "Laddu" "Lassi"
## [137] "Lauki ke kofte" "Lauki ki subji"
## [139] "Ledikeni" "Lilva Kachori"
## [141] "Litti chokha" "Luchi"
## [143] "Lyangcha" "Maach Jhol"
## [145] "Mag Dhokli" "Mahim halwa"
## [147] "Makki di roti sarson da saag" "Malapua"
## [149] "Masala Dosa" "Masor Koni"
## [151] "Masor tenga" "Mawa Bati"
## [153] "Methi na Gota" "Mihidana"
## [155] "Mishti Chholar Dal" "Misi roti"
## [157] "Misti doi" "Modak"
## [159] "Mohanthal" "Mushroom do pyaza"
## [161] "Mushroom matar" "Muthiya"
## [163] "Mysore pak" "Naan"
## [165] "Namakpara" "Nankhatai"
## [167] "Navrattan korma" "Obbattu holige"
## [169] "Pachadi" "Pakhala"
## [171] "Palak paneer" "Palathalikalu"
## [173] "Paneer butter masala" "Paneer tikka masala"
## [175] "Pani Pitha" "Pani puri"
## [177] "Paniyaram" "Panjeeri"
## [179] "Pantua" "Papad"
## [181] "Papadum" "Paratha"
## [183] "Paravannam" "Paruppu sadam"
## [185] "Patra" "Pattor"
## [187] "Pav Bhaji" "Payasam"
## [189] "Payokh" "Pesarattu"
## [191] "Petha" "Phirni"
## [193] "Pinaca" "Pindi chana"
## [195] "Pithe" "Poha"
## [197] "Pongal" "Poornalu"
## [199] "Pootharekulu" "Poriyal"
## [201] "Pork Bharta" "Prawn malai curry"
## [203] "Puli sadam" "Puri Bhaji"
## [205] "Puttu" "Qubani ka meetha"
## [207] "Rabri" "Rajma chaval"
## [209] "Ras malai" "Rasabali"
## [211] "Rasam" "Rasgulla"
## [213] "Red Rice" "Rongi"
## [215] "Saath" "Sabudana Khichadi"
## [217] "Sambar" "Samosa"
## [219] "Sandesh" "Sandige"
## [221] "Sattu ki roti" "Sev khamani"
## [223] "Sev tameta" "Sevai"
## [225] "Shahi paneer" "Shahi tukra"
## [227] "Shankarpali" "Sheer korma"
## [229] "Sheera" "Shrikhand"
## [231] "Shufta" "Shukto"
## [233] "Singori" "Sohan halwa"
## [235] "Sohan papdi" "Sukhdi"
## [237] "Surnoli" "Sutar feni"
## [239] "Tandoori Chicken" "Tandoori Fish Tikka"
## [241] "Thalipeeth" "Thayir sadam"
## [243] "Theeyal" "Thepla"
## [245] "Til Pitha" "Turiya Patra Vatana sabji"
## [247] "Undhiyu" "Unni Appam"
## [249] "Upma" "Uttapam"
## [251] "Vada" "Veg Kolhapuri"
## [253] "Vegetable jalfrezi" "Vindaloo"
## [255] "Zunka"#decreasing= TRUE for Descending order sort
stringr::str_sort(df$name, decreasing = TRUE)## [1] "Zunka" "Vindaloo"
## [3] "Vegetable jalfrezi" "Veg Kolhapuri"
## [5] "Vada" "Uttapam"
## [7] "Upma" "Unni Appam"
## [9] "Undhiyu" "Turiya Patra Vatana sabji"
## [11] "Til Pitha" "Thepla"
## [13] "Theeyal" "Thayir sadam"
## [15] "Thalipeeth" "Tandoori Fish Tikka"
## [17] "Tandoori Chicken" "Sutar feni"
## [19] "Surnoli" "Sukhdi"
## [21] "Sohan papdi" "Sohan halwa"
## [23] "Singori" "Shukto"
## [25] "Shufta" "Shrikhand"
## [27] "Sheera" "Sheer korma"
## [29] "Shankarpali" "Shahi tukra"
## [31] "Shahi paneer" "Sevai"
## [33] "Sev tameta" "Sev khamani"
## [35] "Sattu ki roti" "Sandige"
## [37] "Sandesh" "Samosa"
## [39] "Sambar" "Sabudana Khichadi"
## [41] "Saath" "Rongi"
## [43] "Red Rice" "Rasgulla"
## [45] "Rasam" "Rasabali"
## [47] "Ras malai" "Rajma chaval"
## [49] "Rabri" "Qubani ka meetha"
## [51] "Puttu" "Puri Bhaji"
## [53] "Puli sadam" "Prawn malai curry"
## [55] "Pork Bharta" "Poriyal"
## [57] "Pootharekulu" "Poornalu"
## [59] "Pongal" "Poha"
## [61] "Pithe" "Pindi chana"
## [63] "Pinaca" "Phirni"
## [65] "Petha" "Pesarattu"
## [67] "Payokh" "Payasam"
## [69] "Pav Bhaji" "Pattor"
## [71] "Patra" "Paruppu sadam"
## [73] "Paravannam" "Paratha"
## [75] "Papadum" "Papad"
## [77] "Pantua" "Panjeeri"
## [79] "Paniyaram" "Pani puri"
## [81] "Pani Pitha" "Paneer tikka masala"
## [83] "Paneer butter masala" "Palathalikalu"
## [85] "Palak paneer" "Pakhala"
## [87] "Pachadi" "Obbattu holige"
## [89] "Navrattan korma" "Nankhatai"
## [91] "Namakpara" "Naan"
## [93] "Mysore pak" "Muthiya"
## [95] "Mushroom matar" "Mushroom do pyaza"
## [97] "Mohanthal" "Modak"
## [99] "Misti doi" "Misi roti"
## [101] "Mishti Chholar Dal" "Mihidana"
## [103] "Methi na Gota" "Mawa Bati"
## [105] "Masor tenga" "Masor Koni"
## [107] "Masala Dosa" "Malapua"
## [109] "Makki di roti sarson da saag" "Mahim halwa"
## [111] "Mag Dhokli" "Maach Jhol"
## [113] "Lyangcha" "Luchi"
## [115] "Litti chokha" "Lilva Kachori"
## [117] "Ledikeni" "Lauki ki subji"
## [119] "Lauki ke kofte" "Lassi"
## [121] "Laddu" "Laapsi"
## [123] "Kuzhi paniyaram" "Kuzhambu"
## [125] "Kuzhakkattai" "Kutchi dabeli"
## [127] "Kumol Sawul" "Kulfi falooda"
## [129] "Kothamali sadam" "Koshimbir"
## [131] "Koshambri" "Kos kootu"
## [133] "Kootu" "Konir Dom"
## [135] "Kombdi vade" "Kolim Jawla"
## [137] "Koldil Duck" "Koldil Chicken"
## [139] "Kofta" "Khorisa"
## [141] "Khichu" "Khichdi"
## [143] "Kheer sagar" "Kheer"
## [145] "Khar" "Khandvi"
## [147] "Khaman" "Khakhra"
## [149] "Keri no ras" "Keerai sadam"
## [151] "Keerai poriyal" "Keerai masiyal"
## [153] "Keerai kootu" "Karela bharta"
## [155] "Kansar" "Kanji"
## [157] "Kalakand" "Kakinada khaja"
## [159] "Kaju katli" "Kajjikaya"
## [161] "Kadhi pakoda" "Kadai paneer"
## [163] "Kachori" "Kabiraji"
## [165] "Kaara kozhambu" "Jeera Aloo"
## [167] "Jalebi" "Imarti"
## [169] "Idli" "Idiappam"
## [171] "Haq Maas" "Handwo"
## [173] "Hando Guri" "Halvasan"
## [175] "Gulab jamun" "Gud papdi"
## [177] "Goja" "Ghooghra"
## [179] "Ghevar" "Gheela Pitha"
## [181] "Gavvalu" "Gatta curry"
## [183] "Galho" "Gajar ka halwa"
## [185] "Farsi Puri" "Fara"
## [187] "Dum aloo" "Dudhi halwa"
## [189] "Double ka meetha" "Dosa"
## [191] "Doodhpak" "Dhondas"
## [193] "Dhokla" "Dharwad pedha"
## [195] "Dalithoy" "Dal tadka"
## [197] "Dal makhani " "Dahi vada"
## [199] "Daal puri" "Daal Dhokli"
## [201] "Daal baati churma" "Currivepillai sadam "
## [203] "Copra paak" "Coconut vadi"
## [205] "Churma Ladoo" "Chorafali"
## [207] "Chole bhature" "Chingri malai curry"
## [209] "Chingri Bhape" "Chikki"
## [211] "Chicken Varuval" "Chicken Tikka masala"
## [213] "Chicken Tikka" "Chicken razala"
## [215] "Chhena poda" "Chhena kheeri"
## [217] "Chhena jalebi" "Chevdo"
## [219] "Cheera Doi" "Chapati"
## [221] "Chana masala" "Cham cham"
## [223] "Chakali" "Chak Hao Kheer"
## [225] "Butter chicken" "Brown Rice"
## [227] "Bora Sawul" "Boondi"
## [229] "Bombil fry" "Black rice"
## [231] "Bisi bele bath" "Biryani"
## [233] "Bilahi Maas" "Bhindi masala"
## [235] "Bhatura" "Bhakri"
## [237] "Bengena Pitika" "Beef Fry"
## [239] "Bebinca" "Basundi"
## [241] "Bandar laddu" "Balu shahi"
## [243] "Bajri no rotlo" "Avial"
## [245] "Attu" "Ariselu"
## [247] "Anarsa" "Amti"
## [249] "Alu Pitika" "Aloo tikki"
## [251] "Aloo shimla mirch" "Aloo methi"
## [253] "Aloo matar" "Aloo gobi"
## [255] "Adhirasam"Capability 3 ggplot2::ggplot
ggplot provides extensive data visualization options which helps to understand the underlying data easily and quickly
library(ggplot2)
df1 <- df %>% group_by(flavor_profile)
ggplot(data = df1, aes(x=df1$flavor_profile, y=df$prep_time)) + geom_bar(stat = "identity", fill = "steelblue") + xlab("Flavors") + ylab("Preparation time") + ggtitle("Flavors with Preparation time") + theme(plot.title = element_text(hjust = 0.5))