Import data
# excel file
data <- read_excel("../00_data/myData.xlsx")
data
## # A tibble: 1,430 × 4
## country food_category consumption co2_emmission
## <chr> <chr> <dbl> <dbl>
## 1 Argentina Pork 10.5 37.2
## 2 Argentina Poultry 38.7 41.5
## 3 Argentina Beef 55.5 1712
## 4 Argentina Lamb & Goat 1.56 54.6
## 5 Argentina Fish 4.36 6.96
## 6 Argentina Eggs 11.4 10.5
## 7 Argentina Milk - inc. cheese 195. 278.
## 8 Argentina Wheat and Wheat Products 103. 19.7
## 9 Argentina Rice 8.77 11.2
## 10 Argentina Soybeans 0 0
## # ℹ 1,420 more rows
Apply the following dplyr verbs to your data
Filter rows
filter(data, country == "Japan")
## # A tibble: 11 × 4
## country food_category consumption co2_emmission
## <chr> <chr> <dbl> <dbl>
## 1 Japan Pork 20.6 73.0
## 2 Japan Poultry 19.4 20.9
## 3 Japan Beef 9.15 282.
## 4 Japan Lamb & Goat 0.14 4.9
## 5 Japan Fish 31.1 49.7
## 6 Japan Eggs 19.2 17.6
## 7 Japan Milk - inc. cheese 72.1 103.
## 8 Japan Wheat and Wheat Products 45.0 8.59
## 9 Japan Rice 59.8 76.6
## 10 Japan Soybeans 7.34 3.3
## 11 Japan Nuts inc. Peanut Butter 2.59 4.58
Arrange rows
arrange(data, consumption)
## # A tibble: 1,430 × 4
## country food_category consumption co2_emmission
## <chr> <chr> <dbl> <dbl>
## 1 Argentina Soybeans 0 0
## 2 Albania Soybeans 0 0
## 3 Kuwait Pork 0 0
## 4 Armenia Soybeans 0 0
## 5 Venezuela Soybeans 0 0
## 6 Croatia Soybeans 0 0
## 7 Paraguay Soybeans 0 0
## 8 Ecuador Soybeans 0 0
## 9 Serbia Soybeans 0 0
## 10 United Arab Emirates Pork 0 0
## # ℹ 1,420 more rows
Select columns
Add columns
Summarize by groups