【发布时间】:2015-12-14 20:17:34
【问题描述】:
为什么函数 ':=' 不使用 'by' 聚合唯一行,而 LHS:RHS 却使用 'by' 聚合?下面是一个包含 20 行数据和 58 个变量的 .csv 文件。一个简单的复制、粘贴、delim = .csv 就可以了。我仍在努力寻找将样本数据发布到 SO 的最佳方式。我的代码的 2 个变体是:
prodMatrix <- so.sample[, ':=' (Count = .N), by = eval(names(so.sample)[2:28])]
---此版本不使用by聚合rowID---
prodMatrix <- so.sample[, (Count = .N), by = eval(names(so.sample)[2:28])]
---此版本确实使用 by 聚合 rowID ---
"CID","NetIncome_length_Auto Advantage","NetIncome_length_Certificates","NetIncome_length_Comm. Share Draft","NetIncome_length_Escrow Shares","NetIncome_length_HE Fixed","NetIncome_length_HE Variable","NetIncome_length_Holiday Club","NetIncome_length_IRA Certificates","NetIncome_length_IRA Shares","NetIncome_length_Indirect Balloon","NetIncome_length_Indirect New","NetIncome_length_Indirect RV","NetIncome_length_Indirect Used","NetIncome_length_Loanline/CR","NetIncome_length_New Auto","NetIncome_length_Non-Owner","NetIncome_length_Personal","NetIncome_length_Preferred Plus Shares","NetIncome_length_Preferred Shares","NetIncome_length_RV","NetIncome_length_Regular Shares","NetIncome_length_S/L Fixed","NetIncome_length_S/L Variable","NetIncome_length_SBA","NetIncome_length_Share Draft","NetIncome_length_Share/CD Secured","NetIncome_length_Used Auto","NetIncome_sum_Auto Advantage","NetIncome_sum_Certificates","NetIncome_sum_Comm. Share Draft","NetIncome_sum_Escrow Shares","NetIncome_sum_HE Fixed","NetIncome_sum_HE Variable","NetIncome_sum_Holiday Club","NetIncome_sum_IRA Certificates","NetIncome_sum_IRA Shares","NetIncome_sum_Indirect Balloon","NetIncome_sum_Indirect New","NetIncome_sum_Indirect RV","NetIncome_sum_Indirect Used","NetIncome_sum_Loanline/CR","NetIncome_sum_New Auto","NetIncome_sum_Non-Owner","NetIncome_sum_Personal","NetIncome_sum_Preferred Plus Shares","NetIncome_sum_Preferred Shares","NetIncome_sum_RV","NetIncome_sum_Regular Shares","NetIncome_sum_S/L Fixed","NetIncome_sum_S/L Variable","NetIncome_sum_SBA","NetIncome_sum_Share Draft","NetIncome_sum_Share/CD Secured","NetIncome_sum_Used Auto","totNI","Count","totalNI"
93,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,-123.2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,212.97,0,0,0,-71.36,0,0,0,49.01,0,0,67.42,6,404.52
114,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,4,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.54,0,0,0,0,0,-285.44,0,0,0,49.01,0,0,-221.89,90,-19970.1
1112,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.23,0,0,0,0,-101.55,0,-71.36,0,0,0,98.02,0,0,-14.66,28,-410.48
5366,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,-22.35,77631,-1735052.85
6078,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,7,0,0,0,1,0,0,0,0,0,0,0,0,-17.44,0,0,0,0,0,0,0,14.54,0,0,0,0,0,-499.52,0,0,0,49.01,0,0,-453.41,3,-1360.23
11684,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,-22.35,77631,-1735052.85
47358,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,-14.43,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,0,0,0,-85.79,3194,-274013.26
193761,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-101.55,0,-71.36,0,0,0,49.01,0,0,-123.9,9973,-1235654.7
232530,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,-22.35,77631,-1735052.85
604897,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,-22.35,77631,-1735052.85
1021309,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,0,0,0,-71.36,43262,-3087176.32
1023633,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,0,0,0,-71.36,43262,-3087176.32
1029726,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.23,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,37.88,8688,329101.44
1040005,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,-22.35,77631,-1735052.85
1040092,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,49.01,0,0,-22.35,77631,-1735052.85
1064453,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.54,0,212.97,0,0,0,-142.72,0,0,0,0,0,0,84.79,49,4154.71
1067508,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,-123.2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,0,0,0,-194.56,4162,-809758.72
1080303,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-71.36,0,0,0,0,0,0,-71.36,43262,-3087176.32
1181005,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,2,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-101.55,0,-142.72,0,0,0,98.02,0,0,-146.25,614,-89797.5
1200484,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-101.55,0,-285.44,0,0,0,0,0,0,-386.99,50,-19349.5
【问题讨论】:
-
为什么要在 ':=' 周围加上引号?
-
使用 := 的函数形式时需要反引号。 SO 保留了反勾号,所以我尝试替换它们。
-
我不明白你的问题。您是否在问为什么
:=的行为与记录的一样? -
关于反引号,请看这里:meta.stackexchange.com/questions/82718/…
-
:= 的函数形式应该产生与 LHS:RHS 形式相同的结果。然而,在这种情况下他们没有,我想知道为什么。
标签: r data.table