r - 有没有办法进行过滤排名以保留完整的数据框？

问题描述

我正在对一个大型data.frame. 有没有办法根据保留完整的过滤标准进行排名data.frame？该代码的工作方式类似于使用dplyr filter结果，但data.frame在mutate

library(tidyverse)

# Data
df <- read.table(sep="\t", text="
namePlayer    groupPosition   minutesTotals   fgmTotals   fgaTotals   
fg3mTotals  fg3aTotals  fg2mTotals  fg2aTotals  ftmTotals   ftaTotals   
orbTotals   drbTotals   trbTotals   astTotals   stlTotals   blkTotals   
tovTotals   pfTotals    ptsTotals
             Anthony Davis  C   1267    353 698  34 105 319 593 236 294 114 340 454 151 58  90   71  86  976
             Bradley Beal   G   1392    336 714  89 262 247 452 137 174  36 148 184 180 47  32   98 115  898
             Damian Lillard G   1347    335 741 117 297 218 444 229 256  30 151 181 219 35  19  104  69 1016
             Giannis Antetokounmpo  F   1146    335 572  12  79 323 493 212 305  83 346 429 207 45  54  145 116  894
             James Harden   G   1261    331 752 162 416 169 336 318 374  26 175 201 291 70  19  189 116 1142
             Joel Embiid    C   1255    330 680  42 142 288 538 295 368  89 413 502 129 21  70  128 125  997
             Kemba Walker   G   1276    324 734 122 335 202 399 171 208  16 142 158 223 48  18   89  61  941
             Kevin Durant   F   1399    383 760  70 192 313 568 274 300  19 274 293 237 32  39  133  74 1110
             LeBron James   F   1178    340 656  68 191 272 465 180 264  32 251 283 243 44  24  116  54  928
             Paul George    F   1271    332 734 119 315 213 419 179 215  56 235 291 146 82  22   99 106  962", header=TRUE, stringsAsFactors=FALSE)

df_calc <- df %>%
  # Overall Rank
  mutate(o_rank = rank(desc(ptsTotals))) %>%
  # Rank by Position
  group_by(groupPosition) %>%
  mutate(position_rank = rank(desc(ptsTotals))) %>%
  ungroup() %>%
  # Conditional Rank
  mutate(custom_rank = ifelse(groupPosition %in% c("G", "F") & position_rank > 3 |
                          groupPosition =="C" & position_rank > 3, rank(desc(ptsTotals)), NA ))


df_calc_correct <-  df %>%
  # Overall Rank
  mutate(o_rank = rank(desc(ptsTotals))) %>%
  # Rank by Position
  group_by(groupPosition) %>%
  mutate(position_rank = rank(desc(ptsTotals))) %>%
  ungroup() %>%
  # Conditional Rank
  filter(groupPosition %in% c("G", "F") & position_rank > 3 |
                            groupPosition =="C" & position_rank > 3) %>% 
  mutate(custom_rank = rank(desc(ptsTotals)))

df_calc
#> # A tibble: 10 x 23
#>    namePlayer groupPosition minutesTotals fgmTotals fgaTotals fg3mTotals
#>    <chr>      <chr>                 <int>     <int>     <int>      <int>
#>  1 "        ~ C                      1267       353       698         34
#>  2 "        ~ G                      1392       336       714         89
#>  3 "        ~ G                      1347       335       741        117
#>  4 "        ~ F                      1146       335       572         12
#>  5 "        ~ G                      1261       331       752        162
#>  6 "        ~ C                      1255       330       680         42
#>  7 "        ~ G                      1276       324       734        122
#>  8 "        ~ F                      1399       383       760         70
#>  9 "        ~ F                      1178       340       656         68
#> 10 "        ~ F                      1271       332       734        119
#> # ... with 17 more variables: fg3aTotals <int>, fg2mTotals <int>,
#> #   fg2aTotals <int>, ftmTotals <int>, ftaTotals <int>, orbTotals <int>,
#> #   drbTotals <int>, trbTotals <int>, astTotals <int>, stlTotals <int>,
#> #   blkTotals <int>, tovTotals <int>, pfTotals <int>, ptsTotals <int>,
#> #   o_rank <dbl>, position_rank <dbl>, custom_rank <dbl>

df_calc_correct
#> # A tibble: 2 x 23
#>   namePlayer groupPosition minutesTotals fgmTotals fgaTotals fg3mTotals
#>   <chr>      <chr>                 <int>     <int>     <int>      <int>
#> 1 "        ~ G                      1392       336       714         89
#> 2 "        ~ F                      1146       335       572         12
#> # ... with 17 more variables: fg3aTotals <int>, fg2mTotals <int>,
#> #   fg2aTotals <int>, ftmTotals <int>, ftaTotals <int>, orbTotals <int>,
#> #   drbTotals <int>, trbTotals <int>, astTotals <int>, stlTotals <int>,
#> #   blkTotals <int>, tovTotals <int>, pfTotals <int>, ptsTotals <int>,
#> #   o_rank <dbl>, position_rank <dbl>, custom_rank <dbl>

由 reprex 包（v0.2.1）于 2019 年 1 月 4 日创建

标签： rdplyr

set.seed(1) df <- data.frame(a = 1:10, b = sample(1:10)) df %>% mutate(custom_rank = { filt <- a %in% 3:5 replace(rep(NA, n()), which(filt), rank(desc(b[filt])))}) # a b custom_rank # 1 1 3 NA # 2 2 4 NA # 3 3 5 2 # 4 4 7 1 # 5 5 2 3 # 6 6 8 NA # 7 7 9 NA # 8 8 6 NA # 9 9 10 NA # 10 10 1 NA

r - 有没有办法进行过滤排名以保留完整的数据框？

问题描述

解决方案

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