Divide it using dplyr::select in a way the two have a common variable, which you could use to join the two.
Batting_1half <- Batting %>% select(playerID:HR)
Batting_2half <- Batting %>% select(playerID:yearID, stint, teamID, RBI:GIDP)Use tidyr::left_join or other joining functions.
left_join(Batting_1half, Batting_2half)## Joining, by = c("playerID", "yearID", "stint", "teamID")## # A tibble: 110,495 × 22
## playerID yearID stint teamID lgID G AB R H X2B X3B HR
## <chr> <int> <int> <fct> <fct> <int> <int> <int> <int> <int> <int> <int>
## 1 abercda01 1871 1 TRO NA 1 4 0 0 0 0 0
## 2 addybo01 1871 1 RC1 NA 25 118 30 32 6 0 0
## 3 allisar01 1871 1 CL1 NA 29 137 28 40 4 5 0
## 4 allisdo01 1871 1 WS3 NA 27 133 28 44 10 2 2
## 5 ansonca01 1871 1 RC1 NA 25 120 29 39 11 3 0
## 6 armstbo01 1871 1 FW1 NA 12 49 9 11 2 1 0
## 7 barkeal01 1871 1 RC1 NA 1 4 0 1 0 0 0
## 8 barnero01 1871 1 BS1 NA 31 157 66 63 10 9 0
## 9 barrebi01 1871 1 FW1 NA 1 5 1 1 1 0 0
## 10 barrofr01 1871 1 BS1 NA 18 86 13 13 2 1 0
## # … with 110,485 more rows, and 10 more variables: RBI <int>, SB <int>,
## # CS <int>, BB <int>, SO <int>, IBB <int>, HBP <int>, SH <int>, SF <int>,
## # GIDP <int>Batting %>% filter(str_detect(playerID, "HR"))## # A tibble: 0 × 22
## # … with 22 variables: playerID <chr>, yearID <int>, stint <int>, teamID <fct>,
## # lgID <fct>, G <int>, AB <int>, R <int>, H <int>, X2B <int>, X3B <int>,
## # HR <int>, RBI <int>, SB <int>, CS <int>, BB <int>, SO <int>, IBB <int>,
## # HBP <int>, SH <int>, SF <int>, GIDP <int>