campus <- tibble::tribble(
~キャンパス, ~学部,
"三田", "文",
"三田", "経済",
"三田", "法",
"三田", "商",
)
campusdep <- tibble::tribble(
~faculty, ~学科,
"文", "人文社会",
"法", "政治",
"法", "法律",
)
depmita_grade <- tibble::tribble(
~学部, ~学年,
"文", 4,
"文", 3,
"文", 2,
"経済", 4,
"経済", 3,
"法", 4,
"法", 3,
"商", 4,
"商", 3,
)
mita_gradedplyr::left_join(dep, campus, dplyr::join_by(faculty == 学部))dplyr::right_join(dep, campus, dplyr::join_by(faculty == 学部))dplyr::inner_join(dep, mita_grade, dplyr::join_by(faculty == 学部))Warning in dplyr::inner_join(dep, mita_grade, dplyr::join_by(faculty == : Detected an unexpected many-to-many relationship between `x` and `y`.
ℹ Row 1 of `x` matches multiple rows in `y`.
ℹ Row 6 of `y` matches multiple rows in `x`.
ℹ If a many-to-many relationship is expected, set `relationship =
"many-to-many"` to silence this warning.dplyr::full_join(dep, mita_grade, dplyr::join_by(faculty == 学部))Warning in dplyr::full_join(dep, mita_grade, dplyr::join_by(faculty == 学部)): Detected an unexpected many-to-many relationship between `x` and `y`.
ℹ Row 1 of `x` matches multiple rows in `y`.
ℹ Row 6 of `y` matches multiple rows in `x`.
ℹ If a many-to-many relationship is expected, set `relationship =
"many-to-many"` to silence this warning.dplyr::semi_join(campus, dep, dplyr::join_by(学部 == faculty))dplyr::anti_join(campus, dep, dplyr::join_by(学部 == faculty))campus_2 <- tibble::tibble(campus = c("三田", "日吉"))
faculty_2 <- tibble::tibble(faculty = c("文", "経済", "法", "商"))
year_2 <- tibble::tibble(year = 1:4)
dplyr::cross_join(campus_2, faculty_2) |>
dplyr::cross_join(year_2)tokyo_00_04 <- tibble::tribble(
~year, ~max_temp, ~min_temp,
2000, 37.8, -0.7,
2001, 38.1, -2.4,
2002, 35.8, -0.3,
2003, 34.3, -0.8,
2004, 39.5, 0.2,
)
tokyo_05_09 <- tibble::tribble(
~year, ~max_temp, ~min_temp,
2005, 36.2, -0.8,
2006, 36.1, -1.5,
2007, 37.5, 0.2,
2008, 35.3, -0.1,
2009, 34.2, 0,
)
tokyo_10_14 <- tibble::tribble(
~year, ~max_temp, ~min_temp,
2010, 37.2, -0.4,
2011, 36.1, -1.1,
2012, 35.7, -1.0,
2013, 38.3, -1.4,
2014, 36.1, -1.3
)
dplyr::bind_rows(tokyo_00_04, tokyo_05_09, tokyo_10_14)year <- tibble::tibble(year = 2000:2014)
max_temp <- tibble::tibble(max_temp = c(37.8, 38.1, 35.8, 34.3, 39.5, 36.2, 36.1, 37.5, 35.3, 34.2, 37.2, 36.1, 35.7, 38.3, 36.1))
min_temp <- tibble::tibble(min_temp = c(-0.7, -2.4, -0.3, -0.8, 0.2, -0.8, -1.5, 0.2, -0.1, 0, -0.4, -1.1, -1, -1.4, -1.3))
dplyr::bind_cols(year, max_temp, min_temp)