Dear all:
I converted the columns (Baci, Meti, Fungii, Protozoai) into integers
(using excel) and then imported the data (.txt) into R. Interestingly, the
other three variables were loaded as INT, but the 'Baci' one continued
as
Num.
I imported the data using the following command line:
X <- read.delim(file.choose(),
header = TRUE,
dec = ".")
Here is the structure of X:
> str(X)
'data.frame': 115 obs. of 5 variables:
$ ID : Factor w/ 61 levels "107ZRED","112BLKW",..: 8
12 15 18 26 27
29 31 32 36 ...
$ Baci : num 2.90e+12 5.55e+11 9.46e+11 8.13e+11 4.06e+11 ...
$ Meti : int 352645997 334146268 767208656 171567266 462747405
414905627 237010514 387480048 214671355 328813226 ...
$ Fungii : int 43645 19009 15998 2189 8972 8240 3133 17922 6156 13746
...
$ Protozoai: int 3220523 1851891 3252462 1665675 34123768 23175015 203685
4261780 43110492 69802572 ...
I need Baci as an integer, and tried to convert it using as.integer
function, but was not successful.
Could anyone please help me to solve this problem.
Thanks,
?
--
Andre
-------------- next part --------------
ID Baci Meti Fungii Protozoai
126BLK 2.90E+12 352645997 43645 3220523
13ZBLK 5.55E+11 334146268 19009 1851891
157BLK 9.46E+11 767208656 15998 3252462
162ZRED 8.13E+11 171567266 2189 1665675
17ZBLKY 4.06E+11 462747405 8972 34123768
184ZBLK 5.75E+11 414905627 8240 23175015
1ZBLKW 3.45E+10 237010514 3133 203685
2094ZBLK 3.49E+11 387480048 17922 4261780
20LZBLK 1.63E+11 214671355 6156 43110492
29ZBLK 3.37E+11 328813226 13746 69802572
2ZBLKG 3.13E+11 564519908 4003 93195958
60ZRED 3.76E+11 145383281 12473 33141411
77BLK 2.92E+11 227643897 13328 306363850
8ZBLK 2.45E+11 565298547 2900 29939862
91ZRED 5.62E+11 472996887 8584 73402283
112BLKW 7.02E+10 475554339 192654 37844605
1226BLK 1.84E+10 239034620 65524 3994847
12ZBLK 6.45E+10 296646742 286966 45244390
134BLK 9.65E+09 201168840 47474 2756770
160ZRED 5.96E+10 193983600 155040 79660710
166ZRED 8.14E+10 315417009 26056 85856558
17ZBLK G 1.88E+11 626249880 74214 17763633
226ZBLK 3.88E+10 181768548 291862 128256576
3ZBLK 2.38E+10 175939117 46015 8351259
58BLK 5.37E+10 304530782 50342 7718372
60ZBLK 4.23E+10 375725507 146473 58960339
72ZRED 9.58E+10 373650117 73205 171268872
7ZBLK 4.78E+10 146490232 17068 171268872
95BLK 4.18E+10 210377292 71368 31213851
9PZRED 7.12E+10 278312630 178204 392574732
107ZRED 1.18E+11 497812799 7074 5212968
129BLK 1.01E+10 172557004 565 373103
150ZRED 1.48E+11 343107486 7869 65118676
168BLK 9.45E+10 298332033 5281 17428719
174ZBLK 6.29E+10 269735103 24635 42532632
185ZRED 7.81E+10 647775276 1973 48855746
2ZBLKY 4.93E+09 35698451 3183 28935576
4089ZBLK 1.94E+10 326852779 1329 520051
438XZRED 7.20E+09 113153909 630 127811
4ZBLK 5.30E+10 248877230 1469 827989
706ZBLK 3.12E+10 151072339 2407 4885127
86BLK 9.39E+10 526984044 417 1034021
86ZRED 5.71E+10 385701592 7834 92440481
89BLK 3.80E+10 297806285 6314 62159379
112XZBLKG 9.56E+11 603355806 5205 199868382
1191ZBLK 4.59E+11 403738704 35115 93137246
122ZRED 2.93E+11 266699375 930 68471595
14ZBLK 8.03E+11 607043335 5570 75196835
15ZBLK 3.99E+11 185346266 1716 26429018
163BLK 7.18E+11 598193580 20475 419543828
175ZRED 2.08E+11 660223375 4421 35481033
1ZBLKY 6.84E+11 472986697 43059 137129730
20SXZBLK 3.16E+11 26119538 20297 8031502
22ZBLK 7.70E+11 823508297 154975 264859084
63ZBLK 2.10E+11 1601226529 13317 44878482
6ZBLK 1.31E+11 110772471 1395 40830068
82ZBLK 1.10E+12 839550736 5368 68087375
92ZBLK 4.32E+11 829679134 14981 98201518
94BLK 1.54E+11 197873442 1680 6800437
126BLK 2.22E+11 209765315 13000 92754991
13ZBLK 6.75E+11 366018180 18291 60965929
157BLK 2.88E+11 227660122 8904 20595699
162ZRED 1.85E+11 372912115 3124 516219
17ZBLKY 1.02E+11 170028711 4288 1391174
184ZBLK 4.28E+11 385951078 18173 142041693
1ZBLKW 1.26E+11 258658827 3974 1096335
2094ZBLK 2.80E+11 299019239 22940 4827333
20LZBLK 3.00E+11 258928407 1865 5996901
29ZBLK 2.75E+11 363091053 6551 7162010
2ZBLKG 4.53E+11 464020273 12748 20250369
60ZRED 2.45E+11 352738870 15630 22315303
77BLK 1.44E+11 342240282 4192 52542312
8ZBLK 6.66E+10 493488493 3308 8744844
91ZRED 3.52E+10 232562927 861 3506357
112BLKW 2.23E+10 261910886 35522 20277307
1226 BLK 2.39E+10 107972216 48447 25703984
12ZBLK 9.52E+09 392721062 21520 24103013
134BLK 1.73E+10 320819409 62156 107809914
160ZRED 1.06E+11 423290206 201494 62173555
166ZRED 2.92E+10 173837762 9813 4325219
17ZBLKG 2.87E+10 108073600 151168 19695454
226ZBLK 3.58E+10 470892623 203516 447240999
3ZBLK 1.98E+10 149631240 5962 758907
58BLK 6.71E+09 98009797 10103 18282903
60ZBLK 4.12E+10 382747754 96469 4348146
7ZBLK 7.97E+09 88160280 79680 0
95BLK 2.98E+10 202534656 33088 51649275
9PZRED 8.24E+10 388722787 274104 50360078
107ZRED 1.59E+11 109157702 170772 3550234
129BLK 7.59E+09 56423562 1081 1655868
150ZRED 5.69E+10 961853511 33383 13049429
168BLK 6.45E+10 858912603 5990 2934900
174ZBLK 2.04E+10 275907178 601 14077017
185ZRED 1.01E+11 659755530 12468 145136849
2ZBLKY 1.74E+11 458456526 1757 1314242
4089ZBLK 1.88E+11 166340053 2227 861368
438XZRED 3.83E+11 146896139 17545 25426282
4ZBLK 3.96E+11 340192787 7375 16393765
706ZBLK 3.35E+11 656715841 45618 16360596
86ZRED 3.58E+11 594300567 3410 6976935
89BLK 3.51E+11 452257311 22147 12239312
112XZBLKG 2.68E+11 32640092 49973 30637702
1191ZBLK 2.64E+11 744630951 6067 40742989
122ZRED 8.69E+11 1949076953 11653 75332032
14ZBLK 9.29E+11 683016842 50505 70023751
15ZBLK 9.35E+11 310951369 11492 73268344
163BLK 5.01E+11 285192250 12751 43365735
175ZRED 1.19E+12 597936244 14100 44029110
20SXZBLK 5.57E+11 903885504 22956 119497274
22ZBLK 2.60E+11 667969933 23005 6043141
63ZBLK 2.98E+11 685111047 3578 23920500
6ZBLK 4.77E+11 543466563 11550 39048343
82ZBLK 2.55E+11 697276518 3153 72481942
92ZBLK 1.95E+11 272494229 48511 60524953
94BLK 1.02E+12 2146559014 104139 258779386
No.>From ?as.integer:"Note that current implementations of R use 32-bit integers for integer vectors, so the range of representable integers is restricted to about +/-2*10^9: doubles can hold much larger integers exactly. " Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Apr 26, 2016 at 10:11 AM, Andr? Luis Neves <andrluis at ualberta.ca> wrote:> Dear all: > > I converted the columns (Baci, Meti, Fungii, Protozoai) into integers > (using excel) and then imported the data (.txt) into R. Interestingly, the > other three variables were loaded as INT, but the 'Baci' one continued as > Num. > > I imported the data using the following command line: > > X <- read.delim(file.choose(), > header = TRUE, > dec = ".") > > Here is the structure of X: > >> str(X) > 'data.frame': 115 obs. of 5 variables: > $ ID : Factor w/ 61 levels "107ZRED","112BLKW",..: 8 12 15 18 26 27 > 29 31 32 36 ... > $ Baci : num 2.90e+12 5.55e+11 9.46e+11 8.13e+11 4.06e+11 ... > $ Meti : int 352645997 334146268 767208656 171567266 462747405 > 414905627 237010514 387480048 214671355 328813226 ... > $ Fungii : int 43645 19009 15998 2189 8972 8240 3133 17922 6156 13746 > ... > $ Protozoai: int 3220523 1851891 3252462 1665675 34123768 23175015 203685 > 4261780 43110492 69802572 ... > > > I need Baci as an integer, and tried to convert it using as.integer > function, but was not successful. > > > Could anyone please help me to solve this problem. > > Thanks, > > > > -- > Andre > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
That is the "impossible" case, since R integers are 32 bit signed (~2?10^9) even in 64 bit R. You can Google for "R arbitrary precision" and look for packages like Ryacas, bit64 or gmp. However, having such large integers stored as integers would not be necessary for most statistical analyses so you should confirm that your analysis cannot be performed using floating point numbers before resorting to that. -- Sent from my phone. Please excuse my brevity. On April 26, 2016 10:11:38 AM PDT, "Andr? Luis Neves" <andrluis at ualberta.ca> wrote:>Dear all: > >I converted the columns (Baci, Meti, Fungii, Protozoai) into integers >(using excel) and then imported the data (.txt) into R. Interestingly, >the >other three variables were loaded as INT, but the 'Baci' one continued >as >Num. > >I imported the data using the following command line: > >X <- read.delim(file.choose(), > header = TRUE, > dec = ".") > >Here is the structure of X: > >> str(X) >'data.frame': 115 obs. of 5 variables: >$ ID : Factor w/ 61 levels "107ZRED","112BLKW",..: 8 12 15 18 26 >27 >29 31 32 36 ... > $ Baci : num 2.90e+12 5.55e+11 9.46e+11 8.13e+11 4.06e+11 ... > $ Meti : int 352645997 334146268 767208656 171567266 462747405 >414905627 237010514 387480048 214671355 328813226 ... >$ Fungii : int 43645 19009 15998 2189 8972 8240 3133 17922 6156 >13746 >... >$ Protozoai: int 3220523 1851891 3252462 1665675 34123768 23175015 >203685 >4261780 43110492 69802572 ... > > >I need Baci as an integer, and tried to convert it using as.integer >function, but was not successful. > > >Could anyone please help me to solve this problem. > >Thanks, > > >? >-- >Andre > > >------------------------------------------------------------------------ > >______________________________________________ >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code.[[alternative HTML version deleted]]
Please respond to the list. It will be obvious why in a second. That's not my threshhold! -- it's R's. Your numeric integers cannot be exactly represented as integers in R. Period. Maybe there are special packages for extended arithmetic that can do this. but someone else would have to help you there. See here for a discussion that might be helpful: http://www.r-bloggers.com/r-in-a-64-bit-world/ Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Apr 26, 2016 at 10:46 AM, Andr? Luis Neves <andrluis at ualberta.ca> wrote:> So, How could I implement this, Bert? > > I really need that the variable be converted unto an integer, and it seems > that my numbers are much higher than that threshold you stated. > > Thanks, > > Andre > > On Tue, Apr 26, 2016 at 11:42 AM, Bert Gunter <bgunter.4567 at gmail.com> > wrote: >> >> No. >> >> From ?as.integer: >> >> "Note that current implementations of R use 32-bit integers for >> integer vectors, so the range of representable integers is restricted >> to about +/-2*10^9: doubles can hold much larger integers exactly. " >> >> Cheers, >> Bert >> >> >> Bert Gunter >> >> "The trouble with having an open mind is that people keep coming along >> and sticking things into it." >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >> >> >> On Tue, Apr 26, 2016 at 10:11 AM, Andr? Luis Neves <andrluis at ualberta.ca> >> wrote: >> > Dear all: >> > >> > I converted the columns (Baci, Meti, Fungii, Protozoai) into integers >> > (using excel) and then imported the data (.txt) into R. Interestingly, >> > the >> > other three variables were loaded as INT, but the 'Baci' one continued >> > as >> > Num. >> > >> > I imported the data using the following command line: >> > >> > X <- read.delim(file.choose(), >> > header = TRUE, >> > dec = ".") >> > >> > Here is the structure of X: >> > >> >> str(X) >> > 'data.frame': 115 obs. of 5 variables: >> > $ ID : Factor w/ 61 levels "107ZRED","112BLKW",..: 8 12 15 18 26 >> > 27 >> > 29 31 32 36 ... >> > $ Baci : num 2.90e+12 5.55e+11 9.46e+11 8.13e+11 4.06e+11 ... >> > $ Meti : int 352645997 334146268 767208656 171567266 462747405 >> > 414905627 237010514 387480048 214671355 328813226 ... >> > $ Fungii : int 43645 19009 15998 2189 8972 8240 3133 17922 6156 >> > 13746 >> > ... >> > $ Protozoai: int 3220523 1851891 3252462 1665675 34123768 23175015 >> > 203685 >> > 4261780 43110492 69802572 ... >> > >> > >> > I need Baci as an integer, and tried to convert it using as.integer >> > function, but was not successful. >> > >> > >> > Could anyone please help me to solve this problem. >> > >> > Thanks, >> > >> > >> > >> > -- >> > Andre >> > >> > ______________________________________________ >> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. > > > > > -- > Andre
Can you explain why you need them as 'integer', A floating point representation can hold a value upto ~4.5e15 as an "integer" keeping the precision that you might need. Jim Holtman Data Munger Guru What is the problem that you are trying to solve? Tell me what you want to do, not how you want to do it. On Tue, Apr 26, 2016 at 1:11 PM, Andr? Luis Neves <andrluis at ualberta.ca> wrote:> Dear all: > > I converted the columns (Baci, Meti, Fungii, Protozoai) into integers > (using excel) and then imported the data (.txt) into R. Interestingly, the > other three variables were loaded as INT, but the 'Baci' one continued as > Num. > > I imported the data using the following command line: > > X <- read.delim(file.choose(), > header = TRUE, > dec = ".") > > Here is the structure of X: > > > str(X) > 'data.frame': 115 obs. of 5 variables: > $ ID : Factor w/ 61 levels "107ZRED","112BLKW",..: 8 12 15 18 26 27 > 29 31 32 36 ... > $ Baci : num 2.90e+12 5.55e+11 9.46e+11 8.13e+11 4.06e+11 ... > $ Meti : int 352645997 334146268 767208656 171567266 462747405 > 414905627 237010514 387480048 214671355 328813226 ... > $ Fungii : int 43645 19009 15998 2189 8972 8240 3133 17922 6156 13746 > ... > $ Protozoai: int 3220523 1851891 3252462 1665675 34123768 23175015 203685 > 4261780 43110492 69802572 ... > > > I need Baci as an integer, and tried to convert it using as.integer > function, but was not successful. > > > Could anyone please help me to solve this problem. > > Thanks, > > > ? > -- > Andre > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
Ok. I`m trying to run a Poisson glmm with an observation-level random
intercept. But I`m getting the following error for the 'Baci' variable:
'Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in
pwrssUpdate'. I guess this message is because the baci variable is not a
an integer, and cannot be transformed into an integer as R has a threshold
of
2x10^9 even in 64 bit R.
It runs fine for the fungii variable.
If you guys want to run the data (attached), the full command is below.
Thanks.
---------------------------------------------
##Import data:
qPCR <- read.delim(file.choose(),
header = TRUE,
dec = ".")
##Load package
library(lme4)
##Other steps:
qPCR$obs <- 1:nrow(qPCR)
qPCR$fID<-as.factor(qPCR$ID)
qPCR$fDiet<-as.factor(qPCR$Diet)
##Run the model:
M1 <- glmer (Baci ~ fDiet + Crossover + (1|fID:Crossover) + (1|obs),
family = poisson, data=qPCR)
Andre
On Tue, Apr 26, 2016 at 2:36 PM, jim holtman <jholtman at gmail.com>
wrote:
> Can you explain why you need them as 'integer', A floating point
> representation can hold a value upto ~4.5e15 as an "integer"
keeping the
> precision that you might need.
>
>
> Jim Holtman
> Data Munger Guru
>
> What is the problem that you are trying to solve?
> Tell me what you want to do, not how you want to do it.
>
> On Tue, Apr 26, 2016 at 1:11 PM, Andr? Luis Neves <andrluis at
ualberta.ca>
> wrote:
>
>> Dear all:
>>
>> I converted the columns (Baci, Meti, Fungii, Protozoai) into integers
>> (using excel) and then imported the data (.txt) into R. Interestingly,
the
>> other three variables were loaded as INT, but the 'Baci' one
continued as
>> Num.
>>
>> I imported the data using the following command line:
>>
>> X <- read.delim(file.choose(),
>> header = TRUE,
>> dec = ".")
>>
>> Here is the structure of X:
>>
>> > str(X)
>> 'data.frame': 115 obs. of 5 variables:
>> $ ID : Factor w/ 61 levels
"107ZRED","112BLKW",..: 8 12 15 18 26 27
>> 29 31 32 36 ...
>> $ Baci : num 2.90e+12 5.55e+11 9.46e+11 8.13e+11 4.06e+11 ...
>> $ Meti : int 352645997 334146268 767208656 171567266 462747405
>> 414905627 237010514 387480048 214671355 328813226 ...
>> $ Fungii : int 43645 19009 15998 2189 8972 8240 3133 17922 6156
13746
>> ...
>> $ Protozoai: int 3220523 1851891 3252462 1665675 34123768 23175015
>> 203685
>> 4261780 43110492 69802572 ...
>>
>>
>> I need Baci as an integer, and tried to convert it using as.integer
>> function, but was not successful.
>>
>>
>> Could anyone please help me to solve this problem.
>>
>> Thanks,
>>
>>
>> ?
>> --
>> Andre
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
--
Andre
-------------- next part --------------
ID Crossover Period Diet Pen Time Baci Fungii fNDF Starch
126BLK 1 1 Forage 1 End1 2.90E+12 43645 3.87056104 1.443771827
13ZBLK 1 1 Forage 1 End1 5.55E+11 19009 3.970286296 1.480970702
157BLK 1 1 Forage 1 End1 9.46E+11 15998 4.114130366 1.534626493
162ZRED 1 1 Forage 1 End1 8.13E+11 2189 3.600760128 1.343132423
17ZBLKY 1 1 Forage 1 End1 4.06E+11 8972 3.79087129 1.414046468
184ZBLK 1 1 Forage 1 End1 5.75E+11 8240 3.815881751 1.42337571
1ZBLKW 1 1 Forage 1 End1 34490836164 3133 3.295433507 1.229241447
2094ZBLK 1 1 Forage 1 End1 3.49E+11 17922 3.737865394 1.394274549
20LZBLK 1 1 Forage 1 End1 1.63E+11 6156 4.007824601 1.494972999
29ZBLK 1 1 Forage 1 End1 3.37E+11 13746 3.59031272 1.339235398
2ZBLKG 1 1 Forage 1 End1 3.13E+11 4003 3.964994752 1.478996884
60ZRED 1 1 Forage 1 End1 3.76E+11 12473 3.477652579 1.297211636
77BLK 1 1 Forage 1 End1 2.92E+11 13328 4.546906317 1.696057799
8ZBLK 1 1 Forage 1 End1 2.45E+11 2900 4.447927304 1.659137284
91ZRED 1 1 Forage 1 End1 5.62E+11 8584 4.118042491 1.536085769
112BLKW 2 1 Forage 2 End1 70249927920 192654 4.024558544 1.501214987
1226BLK 2 1 Forage 2 End1 18390770816 65524 3.933087193 1.467094931
12ZBLK 2 1 Forage 2 End1 64465242768 286966 3.678844325 1.372258889
134BLK 2 1 Forage 2 End1 9652868358 47474 3.902242465 1.455589429
160ZRED 2 1 Forage 2 End1 59600548800 155040 3.853736644 1.437496099
166ZRED 2 1 Forage 2 End1 81366127920 26056 4.037719564 1.506124226
17ZBLK G 2 1 Forage 2 End1 1.88E+11 74214 3.498366487 1.304938205
226ZBLK 2 1 Forage 2 End1 38794514336 291862 3.406420254 1.270641011
3ZBLK 2 1 Forage 2 End1 23837817696 46015 3.865246883 1.441789574
58BLK 2 1 Forage 2 End1 53734722624 50342 4.190382875 1.563069714
60ZBLK 2 1 Forage 2 End1 42301298024 146473 3.628258067 1.353389528
72ZRED 2 1 Forage 2 End1 95837208152 73205 4.123718464 1.538202984
7ZBLK 2 1 Forage 2 End1 47824296528 17068 4.028244534 1.502589911
95BLK 2 1 Forage 2 End1 41780037212 71368 4.099205498 1.529059315
9PZRED 2 1 Forage 2 End1 71202504840 178204 3.380912297 1.261126197
107ZRED 3 1 Grain 3 End1 1.18E+11 7074 2.146324344 3.007347766
129BLK 3 1 Grain 3 End1 10054798609 565 2.372894545 3.324809285
150ZRED 3 1 Grain 3 End1 1.48E+11 7869 2.152246315 3.015645405
168BLK 3 1 Grain 3 End1 94464253180 5281 2.500082872 3.503020716
174ZBLK 3 1 Grain 3 End1 62911040256 24635 2.273695448 3.185815296
185ZRED 3 1 Grain 3 End1 78074111590 1973 1.894214123 2.654100545
2ZBLKY 3 1 Grain 3 End1 4929843844 3183 2.483620769 3.479954645
4089ZBLK 3 1 Grain 3 End1 19370087262 1329 2.213050085 3.100841327
438XZRED 3 1 Grain 3 End1 7196105124 630 2.217241768 3.106714553
4ZBLK 3 1 Grain 3 End1 52954599928 1469 2.217302693 3.10679992
706ZBLK 3 1 Grain 3 End1 31205271204 2407 2.15080847 3.013630752
86BLK 3 1 Grain 3 End1 93866942272 417 2.753545642 3.858163077
86ZRED 3 1 Grain 3 End1 57127597772 7834 2.295665227 3.216598513
89BLK 3 1 Grain 3 End1 37992593088 6314 2.476126918 3.469454547
112XZBLKG 4 1 Grain 4 End1 9.56E+11 5205 1.890716993 2.649200499
1191ZBLK 4 1 Grain 4 End1 4.59E+11 35115 2.043372229 2.863095191
122ZRED 4 1 Grain 4 End1 2.93E+11 930 2.1174456 2.966883971
14ZBLK 4 1 Grain 4 End1 8.03E+11 5570 2.268248698 3.178183517
15ZBLK 4 1 Grain 4 End1 3.99E+11 1716 2.22233515 3.113851206
163BLK 4 1 Grain 4 End1 7.18E+11 20475 2.524745564 3.537577138
175ZRED 4 1 Grain 4 End1 2.08E+11 4421 2.113107696 2.960805865
1ZBLKY 4 1 Grain 4 End1 6.84E+11 43059 2.593311258 3.633648772
20SXZBLK 4 1 Grain 4 End1 3.16E+11 20297 1.878154129 2.631597894
22ZBLK 4 1 Grain 4 End1 7.70E+11 154975 2.263447759 3.171456625
63ZBLK 4 1 Grain 4 End1 2.10E+11 13317 2.444859889 3.425644379
6ZBLK 4 1 Grain 4 End1 1.31E+11 1395 2.630183444 3.685312672
82ZBLK 4 1 Grain 4 End1 1.10E+12 5368 2.102445712 2.945866701
92ZBLK 4 1 Grain 4 End1 4.32E+11 14981 2.137551055 2.995054968
94BLK 4 1 Grain 4 End1 1.54E+11 1680 2.533433557 3.549750423
126BLK 1 2 Forage 1 End2 2.22E+11 13000 4.760093885 1.775579657
13ZBLK 1 2 Forage 1 End2 6.75E+11 18291 4.585536093 1.71046723
157BLK 1 2 Forage 1 End2 2.88E+11 8904 5.286298418 1.971861094
162ZRED 1 2 Forage 1 End2 1.85E+11 3124 4.501846838 1.679250002
17ZBLKY 1 2 Forage 1 End2 1.02E+11 4288 4.722218572 1.761451651
184ZBLK 1 2 Forage 1 End2 4.28E+11 18173 4.787683496 1.785870957
1ZBLKW 1 2 Forage 1 End2 1.26E+11 3974 4.120447496 1.536982868
2094ZBLK 1 2 Forage 1 End2 2.80E+11 22940 5.320906238 1.98477028
20LZBLK 1 2 Forage 1 End2 3.00E+11 1865 4.910904822 1.831834185
29ZBLK 1 2 Forage 1 End2 2.75E+11 6551 4.64713525 1.733444553
2ZBLKG 1 2 Forage 1 End2 4.53E+11 12748 5.216415474 1.945793806
60ZRED 1 2 Forage 1 End2 2.45E+11 15630 4.320339869 1.611545438
77BLK 1 2 Forage 1 End2 1.44E+11 4192 4.946939294 1.845275532
8ZBLK 1 2 Forage 1 End2 66556874137 3308 5.369136284 2.002760742
91ZRED 1 2 Forage 1 End2 35178277612 861 5.194279355 1.937536734
112BLKW 2 2 Grain 2 End2 22345514304 35522 2.189470508 3.067802525
1226 BLK 2 2 Grain 2 End2 23881492608 48447 2.61032416 3.657486601
12ZBLK 2 2 Grain 2 End2 9521876928 21520 2.66964942 3.740610891
134BLK 2 2 Grain 2 End2 17265347752 62156 3.266154115 4.576410507
160ZRED 2 2 Grain 2 End2 1.06E+11 201494 2.801511562 3.925371093
166ZRED 2 2 Grain 2 End2 29245020768 9813 2.633190427 3.689525942
17ZBLKG 2 2 Grain 2 End2 28686200320 151168 2.684194907 3.760991472
226ZBLK 2 2 Grain 2 End2 35823496868 203516 2.656602944 3.722330667
3ZBLK 2 2 Grain 2 End2 19774776776 5962 3.01716587 4.22753768
58BLK 2 2 Grain 2 End2 6712885842 10103 2.776815993 3.890768604
60ZBLK 2 2 Grain 2 End2 41185544916 96469 2.757875102 3.86422935
7ZBLK 2 2 Grain 2 End2 7965902400 79680 2.876690768 4.030709327
95BLK 2 2 Grain 2 End2 29843174520 33088 3.319343593 4.650937575
9PZRED 2 2 Grain 2 End2 82361326080 274104 2.695285046 3.776530553
107ZRED 3 2 Forage 3 End2 1.59E+11 170772 4.574352981 1.706295778
129BLK 3 2 Forage 3 End2 7594466101 1081 5.509799583 2.055230063
150ZRED 3 2 Forage 3 End2 56872492896 33383 4.602932045 1.716956157
168BLK 3 2 Forage 3 End2 64542557920 5990 5.156588126 1.923477393
174ZBLK 3 2 Forage 3 End2 20398760236 601 4.777512847 1.782077167
185ZRED 3 2 Forage 3 End2 1.01E+11 12468 4.531116217 1.690167878
2ZBLKY 3 2 Forage 3 End2 1.74E+11 1757 5.336898548 1.990735629
4089ZBLK 3 2 Forage 3 End2 1.88E+11 2227 4.617405661 1.722355012
438XZRED 3 2 Forage 3 End2 3.83E+11 17545 4.698264622 1.752516503
4ZBLK 3 2 Forage 3 End2 3.96E+11 7375 4.899836763 1.827705648
706ZBLK 3 2 Forage 3 End2 3.35E+11 45618 4.437969639 1.655422939
86ZRED 3 2 Forage 3 End2 3.58E+11 3410 4.810601973 1.79441986
89BLK 3 2 Forage 3 End2 3.51E+11 22147 4.768193587 1.778600956
112XZBLKG 4 2 Grain 4 End2 2.68E+11 49973 2.531626089 3.547217868
1191ZBLK 4 2 Grain 4 End2 2.64E+11 6067 2.63885618 3.697464579
122ZRED 4 2 Grain 4 End2 8.69E+11 11653 2.389283575 3.347772968
14ZBLK 4 2 Grain 4 End2 9.29E+11 50505 2.780220526 3.895538906
15ZBLK 4 2 Grain 4 End2 9.35E+11 11492 2.662929278 3.731194885
163BLK 4 2 Grain 4 End2 5.01E+11 12751 2.616739418 3.666475416
175ZRED 4 2 Grain 4 End2 1.19E+12 14100 2.539769021 3.558627433
20SXZBLK 4 2 Grain 4 End2 5.57E+11 22956 2.310979313 3.238056024
22ZBLK 4 2 Grain 4 End2 2.60E+11 23005 2.772700065 3.885001523
63ZBLK 4 2 Grain 4 End2 2.98E+11 3578 2.921279989 4.093186042
6ZBLK 4 2 Grain 4 End2 4.77E+11 11550 2.511694326 3.519290242
82ZBLK 4 2 Grain 4 End2 2.55E+11 3153 2.781770351 3.897710461
92ZBLK 4 2 Grain 4 End2 1.95E+11 48511 2.666117852 3.735662593
94BLK 4 2 Grain 4 End2 1.02E+12 104139 2.966186797 4.156107749