Import data

# excel file
data <- read_excel("data/MyData.xlsx")
data
## # A tibble: 2,657 × 10
##      REF Compan…¹ Compa…² Revie…³ Count…⁴ Speci…⁵ Cocoa…⁶ Ingre…⁷ Most …⁸ Rating
##    <dbl> <chr>    <chr>     <dbl> <chr>   <chr>     <dbl> <chr>   <chr>    <dbl>
##  1  2454 5150     U.S.A.     2019 Tanzan… Kokoa …    0.76 3- B,S… rich c…   3.25
##  2  2458 5150     U.S.A.     2019 Domini… Zorzal…    0.76 3- B,S… cocoa,…   3.5 
##  3  2454 5150     U.S.A.     2019 Madaga… Bejofo…    0.76 3- B,S… cocoa,…   3.75
##  4  2542 5150     U.S.A.     2021 Fiji    Matasa…    0.68 3- B,S… chewy,…   3   
##  5  2546 5150     U.S.A.     2021 Venezu… Sur de…    0.72 3- B,S… fatty,…   3   
##  6  2546 5150     U.S.A.     2021 Uganda  Semuli…    0.8  3- B,S… mildly…   3.25
##  7  2542 5150     U.S.A.     2021 India   Anamal…    0.68 3- B,S… milk b…   3.5 
##  8  2808 20N | 2… France     2022 Venezu… Chuao,…    0.78 2- B,S  sandy,…   2.75
##  9  2808 20N | 2… France     2022 Venezu… Chuao,…    0.78 2- B,S  sl. dr…   3   
## 10   797 A. Morin France     2012 Bolivia Bolivia    0.7  4- B,S… vegeta…   3.5 
## # … with 2,647 more rows, and abbreviated variable names
## #   ¹​`Company Manufacturer`, ²​`Company Location`, ³​`Review Date`,
## #   ⁴​`Country of Bean Origin`, ⁵​`Specific Bean Origin or Bar Name`,
## #   ⁶​`Cocoa Percent`, ⁷​Ingredients, ⁸​`Most Memorable Characteristics`

Plot Data

data %>%
    
    ggplot(aes(`Review Date`)) +
    geom_bar()