如何根据另一列的条件创建新列，但输出超出二进制值
[英]How to create a new column based on condition from another column, but with outputs beyond binary values
问题描述
So, I have a tool data on some basic football players' statistics.
所以，我有一个关于一些基本足球运动员统计数据的工具数据。 I want to classify leagues based on their difficulty between 1 and 0.4.我想根据 1 到 0.4 之间的难度对联赛进行分类。 If I use ifelse statement, I believe I will get binary responses, and I want, at least, 4 "levels" on this new column (League difficulty).如果我使用ifelse语句，我相信我会得到二进制响应，并且我希望在这个新列（联盟难度）上至少有 4 个“级别”。 How could I do that?我怎么能那样做？
Data example:数据示例：
Player Season Team League Goals
<chr> <chr> <chr> <chr> <dbl>
1 L. Messi 14-15 Barcelona La Liga 59
2 Luis Suárez 14-15 Barcelona La Liga 19
3 Neymar 14-15 Barcelona La Liga 41
4 A. Griezmann 14-15 Atletico La Liga 24
5 Cristiano Ronaldo 14-15 Real Madrid La Liga 61
6 M. Antonio 14-15 Nottingham Championship 15
7 K. Benzema 14-15 Real Madrid La Liga 17
8 G. Bale 14-15 Real Madrid La Liga 13
9 A. Adúriz 14-15 Athletic La Liga 23
10 C. Bacca 14-15 Sevilla La Liga 28
11 Iago Aspas 14-15 Sevilla La Liga 7
12 P. Alcacér 14-15 Valencia La Liga 13
13 M. Götze 14-15 Bayern Bundesliga 16
14 R. Lewandowski 14-15 Bayern Bundesliga 24
15 A. Robben 14-15 Bayern Bundesliga 16
16 Thomas Müller 14-15 Bayern Bundesliga 20
17 T. Werner 14-15 Augsburg Bundesliga 8
18 M. Kruse 14-15 Monchengladbach Bundesliga 11
19 L. Stindl 14-15 Monchengladbach Bundesliga 10
20 I. Perisic 14-15 Wolfsburg Bundesliga 9
21 B. Dost 14-15 Wolfsburg Bundesliga 19
22 K. De Bruyne 14-15 Wolfsburg Bundesliga 17
23 K. Volland 14-15 Hoffenheim Bundesliga 10
24 Roberto Firmino 14-15 Hoffenheim Bundesliga 12
25 Heng Min Son 14-15 Bayer Leverkusen Bundesliga 12
26 L. Sané 14-15 Schalke Bundesliga 4
27 P. Aubameyang 14-15 Borussia Bundesliga 22
28 M. Reus 14-15 Borussia Bundesliga 11
29 C. Immobile 14-15 Borussia Bundesliga 10
30 Hulk 14-15 Zenit Russian PL 18
31 S. Rondón 14-15 Zenit Russian PL 18
32 S. Azmoun 14-15 Rubin Russian PL 2
33 A. Dzyuba 14-15 Spartak Russian PL 5
34 M. Icardi 14-15 Inter Serie A 26
35 M. Hamsik 14-15 Napoli Serie A 14
36 D. Mertens 14-15 Napoli Serie A 11
37 Jorginho 14-15 Napoli Serie A 1
38 G. Higuaín 14-15 Napoli Serie A 26
39 D. Zapata 14-15 Napoli Serie A 8
40 L. Insigne 14-15 Napoli Serie A 1
41 L. Muriel 14-15 Sampdoria Serie A 4
42 Bruno Fernandes 14-15 Udinese Serie A 3
43 P. Dybala 14-15 Palermo Serie A 14
44 M. Salah 14-15 Fiorentina Serie A 8
45 J. Ilicic 14-15 Atalanta Serie A 9
46 D. Berardi 14-15 Sassuolo Serie A 15
47 João Pedro 14-15 Cagliari Serie A 3
48 A. Candreva 14-15 Lazio Serie A 12
49 F. Quagliarella 14-15 Torino Serie A 14
50 A. Morata 14-15 Juventus Serie A 16
51 P. Pogba 14-15 Juventus Serie A 12
52 K. Coman 14-15 Juventus Serie A 1
So, let's say I want a level for Serie A, another for Premier League, another for La Liga and another for Bundesliga.所以，假设我想要意甲联赛的一个级别，英超联赛的另一个级别，西甲联赛的另一个级别和德甲联赛的另一个级别。
1 个解决方案
解决方案1
0 2022-10-07 22:23:01
You could use several chained ifelse to do that;您可以使用多个链接ifelse来做到这一点； however, it might be easier to do with case_when .但是，使用case_when可能更容易。
library(dplyr)
df |>
mutate(score = case_when(League == "La Liga" ~ 0.6,
League == "Championship" ~ 0.9,
League == "Bundesliga" ~ 0.8,
League == "Russian PL" ~ 0.7,
League == "Serie A" ~ 0.5))
# Player Season Team League Goals score
#1 L.Messi 14-15 Barcelona La Liga 59 0.6
#2 M.Antonio 14-15 Nottingham Championship 15 0.9
#3 M.Götze 14-15 Bayern Bundes liga 16 0.8
#4 Hulk 14-15 Zenit Russian PL 18 0.7
#5 M.Hamsik 14-15 Napoli Serie A 14 0.5
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