Mengaktifkan fungsi

library(tidyverse)

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Mempersiapkan File Data

url <- "https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-01/key_crop_yields.csv"

df_crop <- read_csv(url)

## Rows: 13075 Columns: 14
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (2): Entity, Code
## dbl (12): Year, Wheat (tonnes per hectare), Rice (tonnes per hectare), Maize...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Melihat Data

glimpse(df_crop)

## Rows: 13,075
## Columns: 14
## $ Entity                             <chr> "Afghanistan", "Afghanistan", "Afgh…
## $ Code                               <chr> "AFG", "AFG", "AFG", "AFG", "AFG", …
## $ Year                               <dbl> 1961, 1962, 1963, 1964, 1965, 1966,…
## $ `Wheat (tonnes per hectare)`       <dbl> 1.0220, 0.9735, 0.8317, 0.9510, 0.9…
## $ `Rice (tonnes per hectare)`        <dbl> 1.5190, 1.5190, 1.5190, 1.7273, 1.7…
## $ `Maize (tonnes per hectare)`       <dbl> 1.4000, 1.4000, 1.4260, 1.4257, 1.4…
## $ `Soybeans (tonnes per hectare)`    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `Potatoes (tonnes per hectare)`    <dbl> 8.6667, 7.6667, 8.1333, 8.6000, 8.8…
## $ `Beans (tonnes per hectare)`       <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `Peas (tonnes per hectare)`        <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `Cassava (tonnes per hectare)`     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `Barley (tonnes per hectare)`      <dbl> 1.0800, 1.0800, 1.0800, 1.0857, 1.0…
## $ `Cocoa beans (tonnes per hectare)` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `Bananas (tonnes per hectare)`     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA,…

df_crop

## # A tibble: 13,075 × 14
##    Entity      Code   Year `Wheat (tonnes per hectare)` Rice (tonnes per hecta…¹
##    <chr>       <chr> <dbl>                        <dbl>                    <dbl>
##  1 Afghanistan AFG    1961                        1.02                      1.52
##  2 Afghanistan AFG    1962                        0.974                     1.52
##  3 Afghanistan AFG    1963                        0.832                     1.52
##  4 Afghanistan AFG    1964                        0.951                     1.73
##  5 Afghanistan AFG    1965                        0.972                     1.73
##  6 Afghanistan AFG    1966                        0.867                     1.52
##  7 Afghanistan AFG    1967                        1.12                      1.92
##  8 Afghanistan AFG    1968                        1.16                      1.95
##  9 Afghanistan AFG    1969                        1.19                      1.98
## 10 Afghanistan AFG    1970                        0.956                     1.81
## # ℹ 13,065 more rows
## # ℹ abbreviated name: ¹`Rice (tonnes per hectare)`
## # ℹ 9 more variables: `Maize (tonnes per hectare)` <dbl>,
## #   `Soybeans (tonnes per hectare)` <dbl>,
## #   `Potatoes (tonnes per hectare)` <dbl>, `Beans (tonnes per hectare)` <dbl>,
## #   `Peas (tonnes per hectare)` <dbl>, `Cassava (tonnes per hectare)` <dbl>,
## #   `Barley (tonnes per hectare)` <dbl>, …

SOAL 1

Menampilkan kolom Entity, Year, Potatoes, dan Cassava saja

select_df <- select(df_crop, Entity, Year, `Potatoes (tonnes per hectare)`, `Cassava (tonnes per hectare)`)

select_df

## # A tibble: 13,075 × 4
##    Entity       Year `Potatoes (tonnes per hectare)` Cassava (tonnes per hecta…¹
##    <chr>       <dbl>                           <dbl>                       <dbl>
##  1 Afghanistan  1961                            8.67                          NA
##  2 Afghanistan  1962                            7.67                          NA
##  3 Afghanistan  1963                            8.13                          NA
##  4 Afghanistan  1964                            8.6                           NA
##  5 Afghanistan  1965                            8.8                           NA
##  6 Afghanistan  1966                            9.07                          NA
##  7 Afghanistan  1967                            9.8                           NA
##  8 Afghanistan  1968                           10                             NA
##  9 Afghanistan  1969                           10.2                           NA
## 10 Afghanistan  1970                            9.54                          NA
## # ℹ 13,065 more rows
## # ℹ abbreviated name: ¹`Cassava (tonnes per hectare)`

SOAL 2

Mengeliminasi kolom Soybeans, Beans, dan Peas dari tabel

select(df_crop, -c(`Soybeans (tonnes per hectare)`, `Beans (tonnes per hectare)`, `Peas (tonnes per hectare)`))

## # A tibble: 13,075 × 11
##    Entity      Code   Year `Wheat (tonnes per hectare)` Rice (tonnes per hecta…¹
##    <chr>       <chr> <dbl>                        <dbl>                    <dbl>
##  1 Afghanistan AFG    1961                        1.02                      1.52
##  2 Afghanistan AFG    1962                        0.974                     1.52
##  3 Afghanistan AFG    1963                        0.832                     1.52
##  4 Afghanistan AFG    1964                        0.951                     1.73
##  5 Afghanistan AFG    1965                        0.972                     1.73
##  6 Afghanistan AFG    1966                        0.867                     1.52
##  7 Afghanistan AFG    1967                        1.12                      1.92
##  8 Afghanistan AFG    1968                        1.16                      1.95
##  9 Afghanistan AFG    1969                        1.19                      1.98
## 10 Afghanistan AFG    1970                        0.956                     1.81
## # ℹ 13,065 more rows
## # ℹ abbreviated name: ¹`Rice (tonnes per hectare)`
## # ℹ 6 more variables: `Maize (tonnes per hectare)` <dbl>,
## #   `Potatoes (tonnes per hectare)` <dbl>,
## #   `Cassava (tonnes per hectare)` <dbl>, `Barley (tonnes per hectare)` <dbl>,
## #   `Cocoa beans (tonnes per hectare)` <dbl>,
## #   `Bananas (tonnes per hectare)` <dbl>

SOAL 3

Tahun berapa saja hasil panen padi (Rice) di Indonesia yang nilainya di bawah 2 ton?

df_crop %>%
  filter(Entity == "Indonesia", `Rice (tonnes per hectare)` < 2) %>% 
  select(Year)

## # A tibble: 7 × 1
##    Year
##   <dbl>
## 1  1961
## 2  1962
## 3  1963
## 4  1964
## 5  1965
## 6  1966
## 7  1967

SOAL 4

Negara apa saja yang punya hasil gandum (Wheat) di atas 5 ton pada tahun 2000 ke atas?

df_crop %>%
  filter(`Wheat (tonnes per hectare)`  > 5, Year >= 2000) %>%
  group_by(Entity) %>% 
  distinct(Entity)

## # A tibble: 36 × 1
## # Groups:   Entity [36]
##    Entity         
##    <chr>          
##  1 Austria        
##  2 Belgium        
##  3 Bulgaria       
##  4 Central America
##  5 Chile          
##  6 China          
##  7 Croatia        
##  8 Czech Republic 
##  9 Denmark        
## 10 Eastern Asia   
## # ℹ 26 more rows

SOAL 5

Bagaimana cara memunculkan data negara Indonesia dan Malaysia khusus untuk tahun 2015 saja?

df_crop %>% 
  filter(Entity %in% c("Indonesia","Malaysia"), Year == 2015)

## # A tibble: 2 × 14
##   Entity    Code   Year `Wheat (tonnes per hectare)` `Rice (tonnes per hectare)`
##   <chr>     <chr> <dbl>                        <dbl>                       <dbl>
## 1 Indonesia IDN    2015                           NA                        5.34
## 2 Malaysia  MYS    2015                           NA                        4.02
## # ℹ 9 more variables: `Maize (tonnes per hectare)` <dbl>,
## #   `Soybeans (tonnes per hectare)` <dbl>,
## #   `Potatoes (tonnes per hectare)` <dbl>, `Beans (tonnes per hectare)` <dbl>,
## #   `Peas (tonnes per hectare)` <dbl>, `Cassava (tonnes per hectare)` <dbl>,
## #   `Barley (tonnes per hectare)` <dbl>,
## #   `Cocoa beans (tonnes per hectare)` <dbl>,
## #   `Bananas (tonnes per hectare)` <dbl>

SOAL 6

Negara mana yang punya hasil jagung (Maize) paling rendah di tahun 2020?

df_crop %>% 
  filter(Year == 2020)  %>%
  arrange(`Maize (tonnes per hectare)`)  %>%
  head(1)

## # A tibble: 0 × 14
## # ℹ 14 variables: Entity <chr>, Code <chr>, Year <dbl>,
## #   Wheat (tonnes per hectare) <dbl>, Rice (tonnes per hectare) <dbl>,
## #   Maize (tonnes per hectare) <dbl>, Soybeans (tonnes per hectare) <dbl>,
## #   Potatoes (tonnes per hectare) <dbl>, Beans (tonnes per hectare) <dbl>,
## #   Peas (tonnes per hectare) <dbl>, Cassava (tonnes per hectare) <dbl>,
## #   Barley (tonnes per hectare) <dbl>, Cocoa beans (tonnes per hectare) <dbl>,
## #   Bananas (tonnes per hectare) <dbl>

Tidak bisa dilakukan karena semua data berada dibawah tahun 2020

SOAL 7

Mengurutkan data Indonesia dari hasil kentang (Potatoes) yang paling tinggi.

df_crop %>%
  filter(Code=="IDN", !is.na(`Potatoes (tonnes per hectare)`)) %>%
  arrange(desc(`Potatoes (tonnes per hectare)`)) %>%
  select(Year, `Potatoes (tonnes per hectare)`)

## # A tibble: 58 × 2
##     Year `Potatoes (tonnes per hectare)`
##    <dbl>                           <dbl>
##  1  2018                            18.7
##  2  2016                            18.3
##  3  2015                            18.2
##  4  2014                            17.7
##  5  2006                            16.9
##  6  2008                            16.7
##  7  1995                            16.6
##  8  2012                            16.6
##  9  2009                            16.5
## 10  2005                            16.4
## # ℹ 48 more rows

SOAL 8

Membuat kolom Rice_Status berisi teks “Tinggi” jika padi > 4 ton, dan “Rendah” jika di bawahnya.

df_crop %>% 
mutate(Rice_Status = ifelse(`Rice (tonnes per hectare)` > 4,"Tinggi", "Rendah")) %>% 
select(Entity,Year,Rice_Status)

## # A tibble: 13,075 × 3
##    Entity       Year Rice_Status
##    <chr>       <dbl> <chr>      
##  1 Afghanistan  1961 Rendah     
##  2 Afghanistan  1962 Rendah     
##  3 Afghanistan  1963 Rendah     
##  4 Afghanistan  1964 Rendah     
##  5 Afghanistan  1965 Rendah     
##  6 Afghanistan  1966 Rendah     
##  7 Afghanistan  1967 Rendah     
##  8 Afghanistan  1968 Rendah     
##  9 Afghanistan  1969 Rendah     
## 10 Afghanistan  1970 Rendah     
## # ℹ 13,065 more rows

SOAL 9

Berapa rata-rata hasil panen pisang (Bananas) di Indonesia dari seluruh tahun yang ada?

df_crop %>% 
   group_by(Code) %>% 
  filter(Code =="IDN",!is.na(`Bananas (tonnes per hectare)`)) %>%
  summarise(`rata-rata hasil panen pisang` = mean(`Bananas (tonnes per hectare)`))

## # A tibble: 1 × 2
##   Code  `rata-rata hasil panen pisang`
##   <chr>                          <dbl>
## 1 IDN                             30.5

SOAL 10

Tampilkan data jagung mulai tahun 2010, lalu menghitung simpangan baku per negara, dan mengurutkannya dari nilai yang paling besar

df_crop %>% 
select(Entity, Code, Year,`Maize (tonnes per hectare)`) %>% filter(Year > 2010)

## # A tibble: 1,923 × 4
##    Entity      Code   Year `Maize (tonnes per hectare)`
##    <chr>       <chr> <dbl>                        <dbl>
##  1 Afghanistan AFG    2011                         1.64
##  2 Afghanistan AFG    2012                         2.20
##  3 Afghanistan AFG    2013                         2.20
##  4 Afghanistan AFG    2014                         2.49
##  5 Afghanistan AFG    2015                         2.15
##  6 Afghanistan AFG    2016                         2.05
##  7 Afghanistan AFG    2017                         1.30
##  8 Afghanistan AFG    2018                         1.47
##  9 Africa      <NA>   2011                         1.95
## 10 Africa      <NA>   2012                         2.01
## # ℹ 1,913 more rows

df_crop %>% 
  group_by(Entity) %>% 
  filter(Year >= 2010, !is.na(`Maize (tonnes per hectare)`)) %>%
  summarise(`Simpangan Baku` = sd(`Maize (tonnes per hectare)`)) %>%
  arrange(desc(`Simpangan Baku`))

## # A tibble: 202 × 2
##    Entity                           `Simpangan Baku`
##    <chr>                                       <dbl>
##  1 Kuwait                                       9.24
##  2 United Arab Emirates                         9.19
##  3 Jordan                                       7.03
##  4 Israel                                       4.80
##  5 Saint Vincent and the Grenadines             2.89
##  6 Qatar                                        2.74
##  7 French Guiana                                2.50
##  8 New Caledonia                                2.29
##  9 Slovakia                                     1.68
## 10 Oman                                         1.61
## # ℹ 192 more rows

Praktik 1

Syarifah Zainab

2026-05-22

Mengaktifkan fungsi

Mempersiapkan File Data

Melihat Data

SOAL 1

Menampilkan kolom Entity, Year, Potatoes, dan Cassava saja

SOAL 2

Mengeliminasi kolom Soybeans, Beans, dan Peas dari tabel

SOAL 3

Tahun berapa saja hasil panen padi (Rice) di Indonesia yang nilainya di bawah 2 ton?

SOAL 4

Negara apa saja yang punya hasil gandum (Wheat) di atas 5 ton pada tahun 2000 ke atas?

SOAL 5

Bagaimana cara memunculkan data negara Indonesia dan Malaysia khusus untuk tahun 2015 saja?

SOAL 6

Negara mana yang punya hasil jagung (Maize) paling rendah di tahun 2020?

Tidak bisa dilakukan karena semua data berada dibawah tahun 2020

SOAL 7

Mengurutkan data Indonesia dari hasil kentang (Potatoes) yang paling tinggi.

SOAL 8

Membuat kolom Rice_Status berisi teks “Tinggi” jika padi > 4 ton, dan “Rendah” jika di bawahnya.

SOAL 9

Berapa rata-rata hasil panen pisang (Bananas) di Indonesia dari seluruh tahun yang ada?

SOAL 10

Tampilkan data jagung mulai tahun 2010, lalu menghitung simpangan baku per negara, dan mengurutkannya dari nilai yang paling besar