R在数据框中添加列，按特征进行季度排名

Question

我想在我的数据框中添加一个按日期排序的新列（在本例中是季度，因此可以按月进行）。公司应按资产排名 quarter/month.

每个季度的公司（id）数量不同，可能有新的进入，也有旧的消失。

我想从这里开始

#   id     assets date
# 1   X1   50   1994-03-31
# 2   X2   120  1994-03-31
# 3   X3   530  1994-03-31
# 4   X4   24   1994-03-31
# 6   X3   57   1994-06-30
# 7   X1   445  1994-06-30
# 8   X10  525  1994-06-30

至此

#   id     assets date      rank
# 1   X1   50   1994-03-31  3
# 2   X2   120  1994-03-31  2
# 3   X3   530  1994-03-31  1
# 4   X4   24   1994-03-31  4
# 6   X3   57   1994-06-30  3
# 7   X1   445  1994-06-30  2
# 8   X10  525  1994-06-30  1

我试过：

temp_asset_rank <- temp_asset_rank %>%
  mutate(yearx = year(date)) %>%
  mutate(month = month(date)) %>%
  group_by(yearx, month) %>%
  mutate(ranking = rank(temp_asset_rank$assets, na.last = NA, ties.method = c("average"))) %>%
  ungroup()

但是 returns:

Error: Column `ranking` must be length 11788 (the group size) or one, not 1188563

如您所见，我的数据集实际上更大并且包含更多列。

改变

group_by(yearx, month)

到

group_by(yearx) %>%
group_by(month)

也不行

你能帮帮我吗？

Answer 1

基础 R 解决方案：

within(df[order(df$assets, decreasing = TRUE),], 
       {rank <- ave(assets, date, FUN = seq.int)})

Tidyverse 解决方案：

library(tidyverse)
df %>% 
  mutate(idx = row_number()) %>% 
  arrange(desc(assets)) %>% 
  group_by(date) %>% 
  mutate(rank = row_number()) %>% 
  ungroup() %>% 
  arrange(idx) %>% 
  select(-idx)

数据：

df <- structure(list(id = c("X1", "X2", "X3", "X4", "X3", "X1", "X10"), 
  assets = c(50L, 120L, 530L, 24L, 57L, 445L, 525L), 
  date = c("1994-03-31", "1994-03-31", "1994-03-31", "1994-03-31", "1994-06-30",
           "1994-06-30", "1994-06-30")), class = "data.frame", row.names = c(NA, -7L))

R在数据框中添加列，按特征进行季度排名

R add column in data frame with quarterly ranking by a characteristic

r

rank

dataframe