如何收集唯一值，并根据条件对其他列求和

Question

我有大量大约一百万行的金融交易数据，我希望能够将其压缩到一个包含唯一用户 ID 列表的新数据框中。然后我希望能够在某些条件下为他们的帐户添加“交易”，即如果 TransactionTypeId == 2 & AC_Type== 19。我会在 excel 中使用 sumifs但是文件的大小意味着它几乎不可能运行在我的电脑上。

df<- structure(list(UserId = c(1, 1, 1, 1, 2, 
2, 2, 3, 3, 3, 4, 5, 6, 
6, 6, 7, 7, 7, 8, 8, 8, 
8, 8, 9, 9, 9, 10, 11, 12, 
12, 13, 13, 13, 14, 14, 15, 15, 
16, 16, 16), TransactionTypeId = c(14, 1, 1, 70, 
15, 1, 1, 14, 1, 1, 70, 14, 14, 1, 1, 14, 1, 1, 14, 1, 1, 1, 
1, 14, 1, 1, 14, 14, 1, 1, 14, 1, 1, 1, 1, 70, 70, 14, 1, 1), 
    AC_Type = c(21, 21, 21, 21, 19, 19, 19, 19, 19, 19, 19, 19, 
    19, 19, 19, 21, 21, 21, 19, 19, 19, 19, 19, 19, 19, 19, 20, 
    19, 19, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20), Trades = c(30, 
    30, 0.00067116, 0.00067115, 249, 249, 0.00533033, 48.75, 
    48.75, 0.00101298, 0.00533, 24.37, 146.25, 146.25, 0.00309109, 
    100.01, 100.01, 0.00233551, 97.5, 90, 0.00189134, 5, 0.00245851, 
    234, 234, 0.00500802, 100.01, 48.75, 48.5, 0.0275474, 24, 
    24, 0.00051975, 100, 0.00223998, 0.00051975, 0.00205, 9.75, 
    8.75, 0.00017811)), row.names = c(NA, -40L), class = c("tbl_df", 
"tbl", "data.frame"))

Answer 1

你可以取sum你要统计的逻辑条件

library(dplyr)

df %>%
  group_by(UserId) %>%
  summarise(count = sum(Trades[TransactionTypeId == 2 & AC_Type== 19]))

Answer 2

不太确定你想要什么...

libary(dplyr)
df %>%
  group_by(UserId) %>%
  filter(TransactionTypeId == 1 & AC_Type == 19) %>%
  summarise(sum = sum(Trades))
# A tibble: 6 x 2
  UserId   sum
   <dbl> <dbl>
1      2 249. 
2      3  48.8
3      6 146. 
4      8  95.0
5      9 234. 
6     12  48.5

给你先group_byUserId，然后filter那些符合你条件的行（注意：我已经把2改成1了示例数据中没有任何 2），最后 summarise 通过对 Trades.

中的值求和

Answer 3

使用data.table

library(data.table)
setDT(df)[, .(count = sum(Trades[TransactionTypeId == 2 & 
     AC_Type== 19], na.rm = TRUE)), UserId]

如何收集唯一值，并根据条件对其他列求和

How to collect unique values, and sum across other columns with conditions

r

unique