Question

我必须创建一个修改过的数据集，将一些行组合在一起。我需要3个要求：

（查看下面的图片以了解列的名称）

相同的“ date_time”，然后
相同的“类型”，然后
总结“数量”列中的行。

我可以手动执行此操作，如您在图像中所见，但是我找不到缩放比例的方法。

任何人都可以帮助什么样的数据处理工具来解决此类问题？

我想改变这个：

：

要复制第一个数据集：

structure(list(date_time = structure(c(1517516099, 1517516099, 
1517516099, 1517516099, 1517516095, 1517516092, 1517516092, 1517516092, 
1517516092, 1517516092, 1517516092, 1517516088, 1517516084, 1517516081, 
1517516074, 1517516073, 1517516071, 1517516068, 1517516061, 1517516053
), class = c("POSIXct", "POSIXt"), tzone = ""), Buyer_from = c("127 - TULLETT PREBON", 
"127 - TULLETT PREBON", "127 - TULLETT PREBON", "3 - XP Investimentos CCTVM S/A", 
"85 - BTG Pactual CTVM S.A.", "85 - BTG Pactual CTVM S.A.", "147 - ATIVA INVESTIMENTOS S.A. CTCV", 
"147 - ATIVA INVESTIMENTOS S.A. CTCV", "147 - ATIVA INVESTIMENTOS S.A. CTCV", 
"147 - ATIVA INVESTIMENTOS S.A. CTCV", "147 - ATIVA INVESTIMENTOS S.A. CTCV", 
"147 - ATIVA INVESTIMENTOS S.A. CTCV", "147 - ATIVA INVESTIMENTOS S.A. CTCV", 
"115 - H.COMMCOR DTVM LTDA", "115 - H.COMMCOR DTVM LTDA", "8 - UBS BRASIL CCTVM S/A", 
"3 - XP Investimentos CCTVM S/A", "8 - UBS BRASIL CCTVM S/A", 
"8 - UBS BRASIL CCTVM S/A", "8 - UBS BRASIL CCTVM S/A"), Price = c(3176.5, 
3176.5, 3176.5, 3176.5, 3177, 3177, 3177.5, 3177.5, 3177.5, 3177.5, 
3177.5, 3177.5, 3177.5, 3177.5, 3177.5, 3178, 3178.5, 3178, 3178, 
3178), Quantity = c(10, 5, 50, 5, 5, 5, 55, 5, 5, 5, 30, 70, 
30, 10, 10, 5, 5, 10, 5, 10), Seller_from = c("85 - BTG Pactual CTVM S.A.", 
"122 - BGC LIQUIDEZ DTVM", "85 - BTG Pactual CTVM S.A.", "3 - XP Investimentos CCTVM S/A", 
"88 - CM Capital Markets CCTVM LTDA", "122 - BGC LIQUIDEZ DTVM", 
"122 - BGC LIQUIDEZ DTVM", "122 - BGC LIQUIDEZ DTVM", "8 - UBS BRASIL CCTVM S/A", 
"8 - UBS BRASIL CCTVM S/A", "92 - RENASCENÇA DTVM LTDA", "92 - RENASCENÇA DTVM LTDA", 
"85 - BTG Pactual CTVM S.A.", "85 - BTG Pactual CTVM S.A.", "122 - BGC LIQUIDEZ DTVM", 
"122 - BGC LIQUIDEZ DTVM", "3 - XP Investimentos CCTVM S/A", 
"77 - CITIGROUP GMB CCTVM S.A.", "386 - RICO INVESTIMENTOS - GRUPO XP", 
"386 - RICO INVESTIMENTOS - GRUPO XP"), Type = structure(c(4L, 
4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 4L, 1L, 4L, 4L, 4L, 1L, 
4L, 4L, 4L), .Label = c("Buyer", "3", "4", "Seller"), class = "factor")), row.names = c(NA, 
20L), class = "data.frame")

Answer 1

这将摆脱您的Seller_from列，但会将其汇总为您的规范：

library(dplyr)
df %>% group_by(date_time, Price, Buyer_from, Type) %>% summarize(Quantity = sum(Quantity))

或在data.table

中

library(data.table)
setDT(df)
df[,.(Quantity = sum(Quantity)),by=.(date_time,Price,Buyer_from,Type)]

使用Dplyr，我可以使您的卖方脱离专栏！

library(dplyr)
#identify what is repeated
df = df %>% group_by(date_time, Buyer_from, Price) %>% mutate(n = n())
#create 2 dataframes to distingiush what is repeated
once = filter(df, n==1)
dups = filter(df, n>1)
#collapse our duplicates
dups = dups %>% group_by(date_time,Buyer_from,Price,Type) %>% summarize(Quantity = sum(Quantity))
#add back our seller_from column
dups$Seller_from = NA

#remove unnecessary columns from nondups
once = select(once, date_time, Buyer_from, Price, Quantity, Seller_from, Type)

#bring everything back together
final = rbind(once,dups)

# Groups:   date_time, Buyer_from, Price [14]
   date_time           Buyer_from                          Price Quantity Seller_from                         Type  
   <dttm>              <chr>                               <dbl>    <dbl> <chr>                               <fct> 
 1 2018-02-01 15:14:59 3 - XP Investimentos CCTVM S/A      3176.        5 3 - XP Investimentos CCTVM S/A      Seller
 2 2018-02-01 15:14:55 85 - BTG Pactual CTVM S.A.          3177         5 88 - CM Capital Markets CCTVM LTDA  Seller
 3 2018-02-01 15:14:52 85 - BTG Pactual CTVM S.A.          3177         5 122 - BGC LIQUIDEZ DTVM             Seller
 4 2018-02-01 15:14:48 147 - ATIVA INVESTIMENTOS S.A. CTCV 3178.       70 92 - RENASCENÇA DTVM LTDA           Seller
 5 2018-02-01 15:14:44 147 - ATIVA INVESTIMENTOS S.A. CTCV 3178.       30 85 - BTG Pactual CTVM S.A.          Buyer 
 6 2018-02-01 15:14:41 115 - H.COMMCOR DTVM LTDA           3178.       10 85 - BTG Pactual CTVM S.A.          Seller
 7 2018-02-01 15:14:34 115 - H.COMMCOR DTVM LTDA           3178.       10 122 - BGC LIQUIDEZ DTVM             Seller
 8 2018-02-01 15:14:33 8 - UBS BRASIL CCTVM S/A            3178         5 122 - BGC LIQUIDEZ DTVM             Seller
 9 2018-02-01 15:14:31 3 - XP Investimentos CCTVM S/A      3178.        5 3 - XP Investimentos CCTVM S/A      Buyer 
10 2018-02-01 15:14:28 8 - UBS BRASIL CCTVM S/A            3178        10 77 - CITIGROUP GMB CCTVM S.A.       Seller
11 2018-02-01 15:14:21 8 - UBS BRASIL CCTVM S/A            3178         5 386 - RICO INVESTIMENTOS - GRUPO XP Seller
12 2018-02-01 15:14:13 8 - UBS BRASIL CCTVM S/A            3178        10 386 - RICO INVESTIMENTOS - GRUPO XP Seller
13 2018-02-01 15:14:52 147 - ATIVA INVESTIMENTOS S.A. CTCV 3178.       45 NA                                  Buyer 
14 2018-02-01 15:14:52 147 - ATIVA INVESTIMENTOS S.A. CTCV 3178.       55 NA                                  Seller
15 2018-02-01 15:14:59 127 - TULLETT PREBON                3176.       65 NA                                  Seller

对具有某些要求的行进行分组

1 个答案: