##Name: nombre del jugador ##Club: club en el que juega ##Nationality: nacionalidad del jugador ##Position: posicion en el campo del jugador ##Age: edad del jugador ##Matches: partidos jugados ##Starts: partifos jugados desde el incio ##Mins: minutos jugados ##Goals: goles realizador por el jugador ##Assists: asistencia realizadas por el jugador ##Passes_Attempted: pases realizados ##Perc_Passes_Completed: pases completados correctamente ##Penalty_Goals: goles de penales ##Penalty_Attempted: penales lanzados ##xG ##xA ##Yellow_Cards: tarjetas amarillas ##Red_Cards: tarjetas rojas
##install.packages("readr")
library(dplyr)##
## Adjuntando el paquete: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(readr) #Para leer archivos .csv
statsplayers <- read_csv("EPL_20_21.csv")## Rows: 532 Columns: 18## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): Name, Club, Nationality, Position
## dbl (14): Age, Matches, Starts, Mins, Goals, Assists, Passes_Attempted, Perc...
##
## 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.head(statsplayers,10) ## # A tibble: 10 × 18
## Name Club Nationality Position Age Matches Starts Mins Goals Assists
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Mason Mo… Chel… ENG MF,FW 21 36 32 2890 6 5
## 2 Edouard … Chel… SEN GK 28 31 31 2745 0 0
## 3 Timo Wer… Chel… GER FW 24 35 29 2602 6 8
## 4 Ben Chil… Chel… ENG DF 23 27 27 2286 3 5
## 5 Reece Ja… Chel… ENG DF 20 32 25 2373 1 2
## 6 César Az… Chel… ESP DF 30 26 24 2188 1 2
## 7 N'Golo K… Chel… FRA MF 29 30 24 2146 0 2
## 8 Jorginho Chel… ITA MF 28 28 23 2010 7 1
## 9 Thiago S… Chel… BRA DF 35 23 23 1935 2 0
## 10 Kurt Zou… Chel… FRA DF 25 24 22 2029 5 0
## # ℹ 8 more variables: Passes_Attempted <dbl>, Perc_Passes_Completed <dbl>,
## # Penalty_Goals <dbl>, Penalty_Attempted <dbl>, xG <dbl>, xA <dbl>,
## # Yellow_Cards <dbl>, Red_Cards <dbl>10 %>% head(statsplayers, .)## # A tibble: 10 × 18
## Name Club Nationality Position Age Matches Starts Mins Goals Assists
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Mason Mo… Chel… ENG MF,FW 21 36 32 2890 6 5
## 2 Edouard … Chel… SEN GK 28 31 31 2745 0 0
## 3 Timo Wer… Chel… GER FW 24 35 29 2602 6 8
## 4 Ben Chil… Chel… ENG DF 23 27 27 2286 3 5
## 5 Reece Ja… Chel… ENG DF 20 32 25 2373 1 2
## 6 César Az… Chel… ESP DF 30 26 24 2188 1 2
## 7 N'Golo K… Chel… FRA MF 29 30 24 2146 0 2
## 8 Jorginho Chel… ITA MF 28 28 23 2010 7 1
## 9 Thiago S… Chel… BRA DF 35 23 23 1935 2 0
## 10 Kurt Zou… Chel… FRA DF 25 24 22 2029 5 0
## # ℹ 8 more variables: Passes_Attempted <dbl>, Perc_Passes_Completed <dbl>,
## # Penalty_Goals <dbl>, Penalty_Attempted <dbl>, xG <dbl>, xA <dbl>,
## # Yellow_Cards <dbl>, Red_Cards <dbl>statsplayers %>%
select(Name, Club, Position, Goals, Mins, Red_Cards)## # A tibble: 532 × 6
## Name Club Position Goals Mins Red_Cards
## <chr> <chr> <chr> <dbl> <dbl> <dbl>
## 1 Mason Mount Chelsea MF,FW 6 2890 0
## 2 Edouard Mendy Chelsea GK 0 2745 0
## 3 Timo Werner Chelsea FW 6 2602 0
## 4 Ben Chilwell Chelsea DF 3 2286 0
## 5 Reece James Chelsea DF 1 2373 0
## 6 César Azpilicueta Chelsea DF 1 2188 1
## 7 N'Golo Kanté Chelsea MF 0 2146 0
## 8 Jorginho Chelsea MF 7 2010 0
## 9 Thiago Silva Chelsea DF 2 1935 1
## 10 Kurt Zouma Chelsea DF 5 2029 0
## # ℹ 522 more rowsstatsplayers %>%
select(Name:Position)## # A tibble: 532 × 4
## Name Club Nationality Position
## <chr> <chr> <chr> <chr>
## 1 Mason Mount Chelsea ENG MF,FW
## 2 Edouard Mendy Chelsea SEN GK
## 3 Timo Werner Chelsea GER FW
## 4 Ben Chilwell Chelsea ENG DF
## 5 Reece James Chelsea ENG DF
## 6 César Azpilicueta Chelsea ESP DF
## 7 N'Golo Kanté Chelsea FRA MF
## 8 Jorginho Chelsea ITA MF
## 9 Thiago Silva Chelsea BRA DF
## 10 Kurt Zouma Chelsea FRA DF
## # ℹ 522 more rowsstatsplayers %>%
select(-'Name', -'Position')## # A tibble: 532 × 16
## Club Nationality Age Matches Starts Mins Goals Assists Passes_Attempted
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Chelsea ENG 21 36 32 2890 6 5 1881
## 2 Chelsea SEN 28 31 31 2745 0 0 1007
## 3 Chelsea GER 24 35 29 2602 6 8 826
## 4 Chelsea ENG 23 27 27 2286 3 5 1806
## 5 Chelsea ENG 20 32 25 2373 1 2 1987
## 6 Chelsea ESP 30 26 24 2188 1 2 2015
## 7 Chelsea FRA 29 30 24 2146 0 2 1504
## 8 Chelsea ITA 28 28 23 2010 7 1 1739
## 9 Chelsea BRA 35 23 23 1935 2 0 1871
## 10 Chelsea FRA 25 24 22 2029 5 0 1720
## # ℹ 522 more rows
## # ℹ 7 more variables: Perc_Passes_Completed <dbl>, Penalty_Goals <dbl>,
## # Penalty_Attempted <dbl>, xG <dbl>, xA <dbl>, Yellow_Cards <dbl>,
## # Red_Cards <dbl>statsPremierGK <- statsplayers %>%
mutate(Position = ifelse(Position == "GK", "SI", "NO"))
head(statsPremierGK)## # A tibble: 6 × 18
## Name Club Nationality Position Age Matches Starts Mins Goals Assists
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Mason Mou… Chel… ENG NO 21 36 32 2890 6 5
## 2 Edouard M… Chel… SEN SI 28 31 31 2745 0 0
## 3 Timo Wern… Chel… GER NO 24 35 29 2602 6 8
## 4 Ben Chilw… Chel… ENG NO 23 27 27 2286 3 5
## 5 Reece Jam… Chel… ENG NO 20 32 25 2373 1 2
## 6 César Azp… Chel… ESP NO 30 26 24 2188 1 2
## # ℹ 8 more variables: Passes_Attempted <dbl>, Perc_Passes_Completed <dbl>,
## # Penalty_Goals <dbl>, Penalty_Attempted <dbl>, xG <dbl>, xA <dbl>,
## # Yellow_Cards <dbl>, Red_Cards <dbl>statsplayers %>%
select(Name, Club, Position, Goals, Mins) %>%
filter(Mins >= 100, Name == 'Harry Kane' | Name == 'Mason Mount')## # A tibble: 2 × 5
## Name Club Position Goals Mins
## <chr> <chr> <chr> <dbl> <dbl>
## 1 Mason Mount Chelsea MF,FW 6 2890
## 2 Harry Kane Tottenham Hotspur FW 23 3082statsplayers %>%
select(Goals, Name) %>%
filter(Goals >= 10) ## # A tibble: 27 × 2
## Goals Name
## <dbl> <chr>
## 1 10 Raheem Sterling
## 2 13 İlkay Gündoğan
## 3 18 Bruno Fernandes
## 4 11 Marcus Rashford
## 5 10 Edinson Cavani
## 6 22 Mohamed Salah
## 7 11 Sadio Mané
## 8 15 Jamie Vardy
## 9 12 Kelechi Iheanacho
## 10 10 Tomáš Souček
## # ℹ 17 more rowsdistinct <- statsplayers %>%
select(Goals, Name) %>%
filter(Goals >= 10) %>%
distinct(Name)
statsplayers %>%
filter(Goals >= 10) %>%
group_by(Goals) %>%
top_n(1, wt = Goals) %>%
ungroup() %>%
arrange(desc(Goals), Name) %>%
head(10)## # A tibble: 10 × 18
## Name Club Nationality Position Age Matches Starts Mins Goals Assists
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Harry Ka… Tott… ENG FW 27 35 35 3082 23 14
## 2 Mohamed … Live… EGY FW 28 37 34 3078 22 5
## 3 Bruno Fe… Manc… POR MF 25 37 35 3099 18 12
## 4 Patrick … Leed… ENG FW 26 38 37 3050 17 7
## 5 Son Heun… Tott… KOR FW 28 37 36 3114 17 10
## 6 Dominic … Ever… ENG FW 23 33 32 2871 16 0
## 7 Jamie Va… Leic… ENG FW 33 34 31 2840 15 9
## 8 Ollie Wa… Asto… ENG FW 24 37 37 3328 14 5
## 9 Alexandr… Arse… FRA FW 29 31 22 1923 13 2
## 10 İlkay Gü… Manc… GER MF 29 28 23 2029 13 2
## # ℹ 8 more variables: Passes_Attempted <dbl>, Perc_Passes_Completed <dbl>,
## # Penalty_Goals <dbl>, Penalty_Attempted <dbl>, xG <dbl>, xA <dbl>,
## # Yellow_Cards <dbl>, Red_Cards <dbl>statsplayers %>%
select(Goals, Name) %>%
count(Name) %>%
arrange(desc(n))## # A tibble: 524 × 2
## Name n
## <chr> <int>
## 1 Ainsley Maitland-Niles 2
## 2 Joe Willock 2
## 3 Mathew Ryan 2
## 4 Robert Snodgrass 2
## 5 Ross Barkley 2
## 6 Ruben Loftus-Cheek 2
## 7 Takumi Minamino 2
## 8 Theo Walcott 2
## 9 Aaron Connolly 1
## 10 Aaron Cresswell 1
## # ℹ 514 more rows