library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.1.6 ✓ dplyr 1.0.7
## ✓ tidyr 1.1.4 ✓ stringr 1.4.0
## ✓ readr 2.1.0 ✓ forcats 0.5.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(stringr)This Data Set had 2580 reviews on the Ramen noodles from The Ramen Rater’s “The Big List.” I want to know which brand, favor, Ramen’s style, brand’s origin based on the rating by the reviewer.
Ramen_DS <- read.csv(file="https://raw.githubusercontent.com/Benson90/Project2/main/ramen-ratings.csv",header = TRUE, sep=",")We were removing some unrated data and converting the character to Numbers.
#remove unrated data
Ramen_DS <- Ramen_DS[!(Ramen_DS$Stars=="Unrated"),]
#convert from char to number
Ramen_DS$Stars <-as.numeric(Ramen_DS$Stars)
head(Ramen_DS)## Review.. Brand
## 1 2580 New Touch
## 2 2579 Just Way
## 3 2578 Nissin
## 4 2577 Wei Lih
## 5 2576 Ching's Secret
## 6 2575 Samyang Foods
## Variety Style Country
## 1 T's Restaurant Tantanmen Cup Japan
## 2 Noodles Spicy Hot Sesame Spicy Hot Sesame Guan-miao Noodles Pack Taiwan
## 3 Cup Noodles Chicken Vegetable Cup USA
## 4 GGE Ramen Snack Tomato Flavor Pack Taiwan
## 5 Singapore Curry Pack India
## 6 Kimchi song Song Ramen Pack South Korea
## Stars Top.Ten
## 1 3.75
## 2 1.00
## 3 2.25
## 4 2.75
## 5 3.75
## 6 4.75Grouping the category and using the data had a minimum of 50 or 10 reviewers.
#Filter out the number of review less than 50 or 10
#Country
Country_counts <- Ramen_DS %>%
group_by(Country) %>%
tally
Frequent_country <- Country_counts %>%
filter(n >= 50) %>%
select(Country)
#Style
Style_counts <- Ramen_DS %>%
group_by(Style) %>%
tally
Frequent_Style <- Style_counts %>%
filter(n >= 50) %>%
select(Style)
#Brand
Brand_counts <- Ramen_DS %>%
group_by(Brand) %>%
tally
Frequent_Brand <- Brand_counts %>%
filter(n >= 50) %>%
select(Brand)By using the sort function and calculating the mean review rate to find the top review from the reviewer.
Ranking_DS <- Ramen_DS %>%
group_by(Country) %>%
filter(Country %in% Frequent_country$Country) %>%
summarize(mean_rate = mean(Stars)) %>%
arrange(desc(mean_rate))
head(Ranking_DS,10)## # A tibble: 10 × 2
## Country mean_rate
## <chr> <dbl>
## 1 Malaysia 4.15
## 2 Singapore 4.13
## 3 Indonesia 4.07
## 4 Japan 3.98
## 5 Hong Kong 3.80
## 6 South Korea 3.79
## 7 Taiwan 3.67
## 8 USA 3.46
## 9 China 3.42
## 10 Thailand 3.38Ranking_DS <- Ramen_DS %>%
group_by(Style) %>%
filter(Style %in% Frequent_Style$Style) %>%
summarize(mean_rate = mean(Stars)) %>%
arrange(desc(mean_rate))
head(Ranking_DS,10)## # A tibble: 4 × 2
## Style mean_rate
## <chr> <dbl>
## 1 Pack 3.70
## 2 Bowl 3.67
## 3 Tray 3.55
## 4 Cup 3.50Ranking_DS <- Ramen_DS %>%
group_by(Brand) %>%
filter(Brand %in% Frequent_Brand$Brand) %>%
summarize(mean_rate = mean(Stars)) %>%
arrange(desc(mean_rate))
head(Ranking_DS,10)## # A tibble: 8 × 2
## Brand mean_rate
## <chr> <dbl>
## 1 Indomie 4.07
## 2 Samyang Foods 4.07
## 3 Paldo 4.02
## 4 Nongshim 4
## 5 Nissin 3.92
## 6 Myojo 3.80
## 7 Mama 3.63
## 8 Maruchan 3.55We found that the reviewer likes Asia-made Ramen. And Reviewer favorite’s style is Ramen in Pack, but the rating difference is in the close gap. Also, the Top 5 favorite brand from a reviewer is Indomie, Samyang Foods, Paldo, Nongshim, and Nissin. Since we are staying in the US, we would like to know what this US-made favorite is. And get to know the top-rating variety of Ramen.
US_Top_DS <- Ramen_DS %>%
filter(Country =="USA") %>%
arrange(desc(Stars))
head(US_Top_DS,10)## Review.. Brand
## 1 2569 Yamachan
## 2 2563 Yamachan
## 3 2559 Jackpot Teriyaki
## 4 2541 Nissin
## 5 2538 Nissin
## 6 2535 Nissin
## 7 2460 Daifuku
## 8 2262 Dream Kitchen
## 9 2248 Nongshim
## 10 2132 Maruchan
## Variety Style Country
## 1 Yokohama Tonkotsu Shoyu Pack USA
## 2 Tokyo Shoyu Ramen Pack USA
## 3 Beef Ramen Pack USA
## 4 Cup Noodles Very Veggie Spicy Chicken Flavor Ramen Noodle Soup Cup USA
## 5 Cup Noodles Very Veggie Beef Flavor Ramen Noodle Soup Cup USA
## 6 Cup Noodles Very Veggie Chicken Flavor Ramen Noodle Soup Cup USA
## 7 Katsuo Bowl Udon Bowl USA
## 8 Curry Flavour Instant Noodles Cup USA
## 9 Shin Noodle Soup Cup USA
## 10 Instant Lunch Chipotle Chicken Flavor Ramen Noodle Soup Cup USA
## Stars Top.Ten
## 1 5
## 2 5
## 3 5
## 4 5
## 5 5
## 6 5
## 7 5
## 8 5
## 9 5
## 10 5Style_Top_DS <- Ramen_DS %>%
filter(Style =="Pack") %>%
arrange(desc(Stars))
head(Style_Top_DS,10)## Review.. Brand
## 1 2570 Tao Kae Noi
## 2 2569 Yamachan
## 3 2566 Nissin
## 4 2563 Yamachan
## 5 2559 Jackpot Teriyaki
## 6 2550 Samyang Foods
## 7 2545 KOKA
## 8 2533 Nongshim
## 9 2528 Prima
## 10 2524 Nissin
## Variety Style Country
## 1 Creamy tom Yum Kung Flavour Pack Thailand
## 2 Yokohama Tonkotsu Shoyu Pack USA
## 3 Demae Ramen Bar Noodle Aka Tonkotsu Flavour Instant Noodle Pack Hong Kong
## 4 Tokyo Shoyu Ramen Pack USA
## 5 Beef Ramen Pack USA
## 6 Paegaejang Ramen Pack South Korea
## 7 Instant Noodles Laksa Singapura Flavour Pack Singapore
## 8 Shin Ramyun Black Pack South Korea
## 9 Juzz's Mee Creamy Chicken Flavour (Export Version) Pack Singapore
## 10 Straits Reborn Laksa Pack Singapore
## Stars Top.Ten
## 1 5
## 2 5
## 3 5
## 4 5
## 5 5
## 6 5
## 7 5
## 8 5
## 9 5
## 10 5Brand_Top_DS <- Ramen_DS %>%
filter(Brand =="Indomie") %>%
arrange(desc(Stars))
head(Brand_Top_DS,5)## Review.. Brand Variety Style Country
## 1 1856 Indomie Instant Cup Noodles Mi Goreng Fried Noodles Cup Indonesia
## 2 863 Indomie Special Fried Curly Noodle (Local) Pack Indonesia
## 3 740 Indomie Mi Goreng Sate (Local) Pack Indonesia
## 4 734 Indomie Mi Goreng Rasa Ayam Panggang Jumbo (Local) Pack Indonesia
## 5 730 Indomie Rasa Soto Banjar Limau Kulit Pack Indonesia
## Stars Top.Ten
## 1 5
## 2 5
## 3 5
## 4 5 \n
## 5 5Brand_Top_DS <- Ramen_DS %>%
filter(Brand =="Samyang Foods") %>%
arrange(desc(Stars))
head(Brand_Top_DS,5)## Review.. Brand Variety Style Country Stars
## 1 2550 Samyang Foods Paegaejang Ramen Pack South Korea 5
## 2 2511 Samyang Foods Samyang Ramen Classic Edition Bowl South Korea 5
## 3 2366 Samyang Foods Buldak Bokkeummyun Snack Pack South Korea 5
## 4 2365 Samyang Foods Stew Buldak Bokkeumtangmyun Pack South Korea 5
## 5 2282 Samyang Foods Gold Jjamppong Fried Noodle Pack South Korea 5
## Top.Ten
## 1
## 2
## 3
## 4
## 5