##install.packages("dplyr")
##install.packages("readr")
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(readr) #Para leer archivos .csv
ufcdata <- read_csv("ufc_fight_stat_data.csv")
## Rows: 14436 Columns: 14
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): ctrl_time, fight_url
## dbl (12): fight_stat_id, fight_id, fighter_id, knockdowns, total_strikes_att...
##
## 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(ufcdata,10)
## # A tibble: 10 × 14
## fight_stat_id fight_id fighter_id knockdowns total_strikes_att
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 14436 7218 2976 0 34
## 2 14435 7218 2884 0 42
## 3 14434 7217 1662 0 59
## 4 14433 7217 2464 0 72
## 5 14432 7216 981 0 130
## 6 14431 7216 179 0 37
## 7 14430 7215 3831 0 105
## 8 14429 7215 2974 0 57
## 9 14428 7214 1108 0 10
## 10 14427 7214 2320 0 10
## # ℹ 9 more variables: total_strikes_succ <dbl>, sig_strikes_att <dbl>,
## # sig_strikes_succ <dbl>, takedown_att <dbl>, takedown_succ <dbl>,
## # submission_att <dbl>, reversals <dbl>, ctrl_time <chr>, fight_url <chr>
ufcdata %>% head
## # A tibble: 6 × 14
## fight_stat_id fight_id fighter_id knockdowns total_strikes_att
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 14436 7218 2976 0 34
## 2 14435 7218 2884 0 42
## 3 14434 7217 1662 0 59
## 4 14433 7217 2464 0 72
## 5 14432 7216 981 0 130
## 6 14431 7216 179 0 37
## # ℹ 9 more variables: total_strikes_succ <dbl>, sig_strikes_att <dbl>,
## # sig_strikes_succ <dbl>, takedown_att <dbl>, takedown_succ <dbl>,
## # submission_att <dbl>, reversals <dbl>, ctrl_time <chr>, fight_url <chr>
10 %>% head(ufcdata, .)
## # A tibble: 10 × 14
## fight_stat_id fight_id fighter_id knockdowns total_strikes_att
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 14436 7218 2976 0 34
## 2 14435 7218 2884 0 42
## 3 14434 7217 1662 0 59
## 4 14433 7217 2464 0 72
## 5 14432 7216 981 0 130
## 6 14431 7216 179 0 37
## 7 14430 7215 3831 0 105
## 8 14429 7215 2974 0 57
## 9 14428 7214 1108 0 10
## 10 14427 7214 2320 0 10
## # ℹ 9 more variables: total_strikes_succ <dbl>, sig_strikes_att <dbl>,
## # sig_strikes_succ <dbl>, takedown_att <dbl>, takedown_succ <dbl>,
## # submission_att <dbl>, reversals <dbl>, ctrl_time <chr>, fight_url <chr>
ufcdata %>%
select(total_strikes_att, knockdowns, sig_strikes_att, ctrl_time)
## # A tibble: 14,436 × 4
## total_strikes_att knockdowns sig_strikes_att ctrl_time
## <dbl> <dbl> <dbl> <chr>
## 1 34 0 32 0:00
## 2 42 0 40 1:28
## 3 59 0 40 7:33
## 4 72 0 55 2:11
## 5 130 0 102 2:03
## 6 37 0 32 2:49
## 7 105 0 80 3:30
## 8 57 0 51 0:33
## 9 10 0 9 1:58
## 10 10 0 9 0:00
## # ℹ 14,426 more rows
ufcdata %>%
select(total_strikes_att:knockdowns, sig_strikes_att=ctrl_time)
## # A tibble: 14,436 × 3
## total_strikes_att knockdowns sig_strikes_att
## <dbl> <dbl> <chr>
## 1 34 0 0:00
## 2 42 0 1:28
## 3 59 0 7:33
## 4 72 0 2:11
## 5 130 0 2:03
## 6 37 0 2:49
## 7 105 0 3:30
## 8 57 0 0:33
## 9 10 0 1:58
## 10 10 0 0:00
## # ℹ 14,426 more rows
ufcdata %>%
select(-knockdowns, -ctrl_time)
## # A tibble: 14,436 × 12
## fight_stat_id fight_id fighter_id total_strikes_att total_strikes_succ
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 14436 7218 2976 34 19
## 2 14435 7218 2884 42 17
## 3 14434 7217 1662 59 37
## 4 14433 7217 2464 72 32
## 5 14432 7216 981 130 90
## 6 14431 7216 179 37 16
## 7 14430 7215 3831 105 63
## 8 14429 7215 2974 57 29
## 9 14428 7214 1108 10 0
## 10 14427 7214 2320 10 8
## # ℹ 14,426 more rows
## # ℹ 7 more variables: sig_strikes_att <dbl>, sig_strikes_succ <dbl>,
## # takedown_att <dbl>, takedown_succ <dbl>, submission_att <dbl>,
## # reversals <dbl>, fight_url <chr>
ufcdata %>%
select(total_strikes_att, knockdowns, sig_strikes_att, ctrl_time) %>%
filter(ctrl_time >= 3, (knockdowns == 2 | total_strikes_att <= 20))
## # A tibble: 104 × 4
## total_strikes_att knockdowns sig_strikes_att ctrl_time
## <dbl> <dbl> <dbl> <chr>
## 1 114 2 97 5:10
## 2 19 0 7 3:09
## 3 19 0 19 4:50
## 4 5 0 1 3:49
## 5 110 2 81 5:54
## 6 106 2 102 3:30
## 7 20 0 14 4:47
## 8 11 0 7 3:13
## 9 128 2 107 4:42
## 10 172 2 161 9:06
## # ℹ 94 more rows
ufcdata %>%
select(total_strikes_att:knockdowns, sig_strikes_att) %>%
filter(knockdowns == 5)
## # A tibble: 2 × 3
## total_strikes_att knockdowns sig_strikes_att
## <dbl> <dbl> <dbl>
## 1 255 5 250
## 2 149 5 83
distinct <- ufcdata %>%
select(total_strikes_att:knockdowns, sig_strikes_att) %>%
filter(knockdowns == 5) %>%
distinct(sig_strikes_att)
ufcdata %>%
select(total_strikes_att:knockdowns, sig_strikes_att) %>%
filter(knockdowns == 5) %>%
group_by(sig_strikes_att) %>%
summarise(sig_strikes_att = mean(sig_strikes_att))
## # A tibble: 2 × 1
## sig_strikes_att
## <dbl>
## 1 83
## 2 250
ufcdata %>%
select(total_strikes_att:knockdowns, sig_strikes_att) %>%
filter(knockdowns == 5) %>%
group_by(sig_strikes_att) %>%
summarise(sig_strikes_att_mean = mean(sig_strikes_att),
total_strikes_att = mean(total_strikes_att),
knockdowns = mean(knockdowns)) %>%
arrange(desc(total_strikes_att), knockdowns) %>%
head(10)
## # A tibble: 2 × 4
## sig_strikes_att sig_strikes_att_mean total_strikes_att knockdowns
## <dbl> <dbl> <dbl> <dbl>
## 1 250 250 255 5
## 2 83 83 149 5
ufcdata %>%
select(total_strikes_att:knockdowns, sig_strikes_att) %>%
count(knockdowns) %>%
arrange(desc(n))
## # A tibble: 7 × 2
## knockdowns n
## <dbl> <int>
## 1 0 11741
## 2 1 2277
## 3 2 314
## 4 3 53
## 5 NA 42
## 6 4 7
## 7 5 2