使用R和dplyr，我有一个汇总的数据框，每天和每位用户都有情绪分数：
date | user | sentiment_score | anger | fear | trust
2016-12-15 | x | -1 | 2 | 1 | 0
2016-12-16 | x | -1 | 0 | 0 | 0
2016-12-15 | y | 1 | 0 | 1 | 0
2016-12-16 | y | -1 | 3 | 0 | 0
2016-12-15 | z | 0 | 0 | 0 | 0
Dput：
df <- structure(list(created_at = structure(c(17150, 17151, 17150,
17151, 17150), class = "Date"), user = c("x", "x", "y", "y",
"z"), sentiment_score = c(-1, -1, 1, -1, 0), anger = c(2, 0,
0, 3, 0), fear = c(1, 0, 1, 0, 0), trust = c(0, 0, 0, 0, 0)), .Names = c("created_at",
"user", "sentiment_score", "anger", "fear", "trust"), class = "data.frame", row.names = c("1900961",
"1900971", "1900981", "1900991", "1901001"))
出于预测目的，我想将此数据帧转换为每天的数据帧，并为每个用户提供单独的情绪分数列（最后列有很多列）：
date | x_sentiment_score | x_anger | x_fear | x_trust| y_sentiment_score | y_anger | y_fear | y_trust| z_sentiment_score | z_anger | z_fear | z_trust
2016-12-15 | -1 | 2 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0
2016-12-16 | -1 | 0 | 0 | 0 | -1 | 3 | 0 | 0 | 0 | 0 | 0 | 0
我很困惑如何实现这一目标。任何建议都将不胜感激。