Import data
# excel file
data <- read_excel("myData.xlsx")
data
## # A tibble: 32,754 × 20
## id original_title original_language overview tagline release_date
## <dbl> <chr> <chr> <chr> <chr> <dttm>
## 1 760161 Orphan: First… en After e… "There… 2022-07-27 00:00:00
## 2 760741 Beast en A recen… "Fight… 2022-08-11 00:00:00
## 3 882598 Smile en After w… "Once … 2022-09-23 00:00:00
## 4 717728 Jeepers Creep… en Forced … "Evil … 2022-09-15 00:00:00
## 5 772450 Presencias es A man w… <NA> 2022-09-07 00:00:00
## 6 1014226 Sonríe es <NA> <NA> 2022-08-18 00:00:00
## 7 913290 Barbarian en In town… "Some … 2022-09-08 00:00:00
## 8 830788 The Invitation en After t… "You a… 2022-08-24 00:00:00
## 9 927341 Hunting Ava B… en Billion… "\"If … 2022-04-01 00:00:00
## 10 762504 Nope en Residen… "What’… 2022-07-20 00:00:00
## # ℹ 32,744 more rows
## # ℹ 14 more variables: title <chr>, popularity <dbl>, revenue <dbl>,
## # budget <dbl>, poster_path <chr>, vote_count <dbl>, vote_average <dbl>,
## # runtime <dbl>, status <chr>, adult <lgl>, backdrop_path <chr>,
## # genre_names <chr>, collection <chr>, collection_name <chr>
Apply the following dplyr verbs to your data
Filter rows
filter(data, original_language == "en")
## # A tibble: 21,923 × 20
## id original_title original_language overview tagline release_date
## <dbl> <chr> <chr> <chr> <chr> <dttm>
## 1 760161 Orphan: First … en After e… "There… 2022-07-27 00:00:00
## 2 760741 Beast en A recen… "Fight… 2022-08-11 00:00:00
## 3 882598 Smile en After w… "Once … 2022-09-23 00:00:00
## 4 717728 Jeepers Creepe… en Forced … "Evil … 2022-09-15 00:00:00
## 5 913290 Barbarian en In town… "Some … 2022-09-08 00:00:00
## 6 830788 The Invitation en After t… "You a… 2022-08-24 00:00:00
## 7 927341 Hunting Ava Br… en Billion… "\"If … 2022-04-01 00:00:00
## 8 762504 Nope en Residen… "What’… 2022-07-20 00:00:00
## 9 836225 The Exorcism o… en An Amer… "God a… 2022-03-11 00:00:00
## 10 801071 The Jack in th… en When a … "Once … 2022-02-24 00:00:00
## # ℹ 21,913 more rows
## # ℹ 14 more variables: title <chr>, popularity <dbl>, revenue <dbl>,
## # budget <dbl>, poster_path <chr>, vote_count <dbl>, vote_average <dbl>,
## # runtime <dbl>, status <chr>, adult <lgl>, backdrop_path <chr>,
## # genre_names <chr>, collection <chr>, collection_name <chr>
Arrange rows
arrange(data, (budget))
## # A tibble: 32,754 × 20
## id original_title original_language overview tagline release_date
## <dbl> <chr> <chr> <chr> <chr> <dttm>
## 1 760161 Orphan: First… en After e… "There… 2022-07-27 00:00:00
## 2 760741 Beast en A recen… "Fight… 2022-08-11 00:00:00
## 3 772450 Presencias es A man w… <NA> 2022-09-07 00:00:00
## 4 1014226 Sonríe es <NA> <NA> 2022-08-18 00:00:00
## 5 927341 Hunting Ava B… en Billion… "\"If … 2022-04-01 00:00:00
## 6 801071 The Jack in t… en When a … "Once … 2022-02-24 00:00:00
## 7 852830 Torn Hearts en A promi… <NA> 2022-05-20 00:00:00
## 8 758724 The Cellar en When Ke… "An an… 2022-03-25 00:00:00
## 9 816952 My Best Frien… en The yea… "True … 2022-09-29 00:00:00
## 10 755566 Day Shift en An LA v… "Some … 2022-08-10 00:00:00
## # ℹ 32,744 more rows
## # ℹ 14 more variables: title <chr>, popularity <dbl>, revenue <dbl>,
## # budget <dbl>, poster_path <chr>, vote_count <dbl>, vote_average <dbl>,
## # runtime <dbl>, status <chr>, adult <lgl>, backdrop_path <chr>,
## # genre_names <chr>, collection <chr>, collection_name <chr>
Select columns
Add columns
Summarize by groups