I am trying to count the unique number of entries in a pivot table.
My pivot table is displayed as such:
U V W X Y Z AA
PN# Customer Offer# Date $ QTY Sum of Offer#
123456 00000001 157815 09.06.2015 16,3 25 1
123456 00000001 157815 09.06.2015 31 10 1
123456 00000001 157815 09.06.2015 43,5 5 1
123456 00000001 157815 09.06.2015 65,3 1 1
123456 00000002 156682 31.03.2015 10 140 1
123456 00000003 157505 19.05.2015 20 25 1
123456 00000004 156925 13.04.2015 10,04 1000 1
123456 00000004 157459 18.05.2015 9,44 1000 1
123456 00000005 158036 23.06.2015 16,3 25 1
123456 00000006 157064 20.04.2015 10,8 100 1
123456 00000006 157064 20.04.2015 12,5 50 1
123456 00000007 156616 26.03.2015 9,5 700 1
123456 00000007 157264 29.04.2015 9,3 450 1
This is basically a list of order offers we make to customers. I want to analyse this to see how often we offer products etc
So far, I have the number of total offers using:
=SUMPRODUCT(--($U$5:$U$7000=U5),$AA$5:$AA$7000)
this shows for one article number, how many offers there are. But of course, it counts the duplicates as well.
So I am testing with COUNTIF:
=SUMPRODUCT(1/COUNTIF($W$5:$W$45,$W$5:$W$45)) (sample fixed range - normally will goto row 7000)
and this works for a fixed range.
So, my question is - how to combine those two? - so that I can see for one Product Number PN#... the unique number of offers made. I can of course then use the same fomula to see unique number of customers, which at present is also not possible.
Thanks!
Related
I have a file with 4 columns separated by space like this bellow:
1_86500000 50 1_87500000 19
1_87500000 13 1_89500000 42
1_89500000 25 1_90500000 10
1_90500000 3 1_91500000 11
1_91500000 23 1_92500000 29
1_92500000 34 1_93500000 4
1_93500000 39 1_94500000 49
1_94500000 35 1_95500000 26
2_35500000 1 2_31500000 81
2_31500000 12 2_4150000 50
The First and Third columns are not in phase so I can not divide the value of one by another.
As there are only two or one possible columns $1 or $3, a solution would be look for the pattern and divide its value in the another column or set it to 0 if there is none like this expected result shows:
P.S. the second field in this expected result is just illustrative to shown the division.
1_86500000 0/50 0
1_87500000 19/13 1.46154
1_89500000 42/25 1.68
1_90500000 10/3 3.333
1_91500000 11/23 0.47826
1_92500000 29/34 0.85294
1_93500000 4/39 0.10256
1_94500000 49/35 1.4
2_35500000 0/1 0
2_31500000 81/12 6.75
2_4150000 50/0 50
I do not archived anything by myself other than this. So I do not have any starting point by now.
I tried separate the fields merged with _ to see if I could match by subtracting the coordinates. If I got 0 would mean that the columns was in phase and correct. But I could not go further.
awk '{if( ($5-$2)==0) print $1,$2,$3,$4,$5,$6}' file
I tried to match both columns but I only got phased results:
awk '{if(($1==$3)) print $1,$4/$2}' file
Can you help me?
awk to the rescue!
$ awk '{d[$1]=$2; n[$3]=$4}
END {for(k in n)
if(k in d) {print k,n[k]"/"d[k],n[k]/d[k]; delete d[k]}
else print k,n[k]"/0",n[k];
for(k in d) print k,"0/"d[k],0}' file | sort
1_86500000 0/50 0
1_87500000 19/13 1.46154
1_89500000 42/25 1.68
1_90500000 10/3 3.33333
1_91500000 11/23 0.478261
1_92500000 29/34 0.852941
1_93500000 4/39 0.102564
1_94500000 49/35 1.4
1_95500000 26/0 26
2_31500000 81/12 6.75
2_35500000 0/1 0
2_4150000 50/0 50
your division by zero result is little strange though!
Explanation keep two arrays for numerator and denominator. Once scanned the file, go over numerator array and find the corresponding denominator and make the division. For the denominators not used apply the convention given.
So I need a bit of help I have a huge excel sheet with materials
Material Quantity
AA 10
BB 11
CC 52
DD 60
AA 16
DD 10
FF 20
QQ 400
RR 25
TT 80
AA 10
AA 122
FF 11
FF 12
GG 1
TT 15
What I would like to be able to do is to select the Value from 1st colum, let's say look for AA and automatically to get the SUM off all the Quantity AA ( In this example 10+16+10+122 = 158)
Although a SUMIF formula does work and might be placed wherever convenient (I have shown #Scott Craner's in D15) a PivotTable (as suggested by #Zahiro Mor) might be a lot more useful, not only because it can sum all Materials at one time but also for further analysis:
I have a bunch of data, ordered below one another in excel (actually openoffice). I need them to be consolidated by the first column, but so that all data are still shown:
From (actually goes until 100):
1 283.038 244
1 279.899 494
1 255.139 992
1 254.606 7329
1 254.5 17145
1 251.008 23278
1 250.723 28758
1 247.753 92703
1 243.43 315278
1 242.928 485029
1 237.475 1226549
1 233.851 2076295
1 232.833 9826327
1 229.656 15965410
1 229.656 30000235
2 286.535 231
2 275.968 496
2 267.927 741
2 262.647 2153
2 258.925 3130
2 253.954 4857
2 249.551 9764
2 244.725 36878
2 243.825 318455
2 242.86 921618
2 238.401 1405028
2 234.984 3170031
2 233.168 4403799
2 229.317 8719139
2 224.395 26986035
2 224.395 30000056
3 269.715 247
3 268.652 469
3 251.214 957
3 249.04 30344
3 245.883 56115
3 241.753 289668
3 241.707 954750
3 240.684 1421766
3 240.178 1865750
3 235.09 2626524
3 233.579 5129755
3 232.517 7018880
3 232.256 18518741
3 228.75 19117443
3 228.75 30000051
to:
1 2 3
283.038 244 286.535 231 269.715 247
279.899 494 275.968 496 268.652 469
255.139 992 267.927 741 251.214 957
254.606 7329 262.647 2153 249.04 30344
254.5 17145 258.925 3130 245.883 56115
251.008 23278 253.954 4857 241.753 289668
250.723 28758 249.551 9764 241.707 954750
247.753 92703 244.725 36878 240.684 1421766
243.43 315278 243.825 318455 240.178 1865750
242.928 485029 242.86 921618 235.09 2626524
237.475 1226549 238.401 1405028 233.579 5129755
233.851 2076295 234.984 3170031 232.517 7018880
232.833 9826327 233.168 4403799 232.256 18518741
229.656 15965410 229.317 8719139 228.75 19117443
229.656 30000235 224.395 26986035 228.75 30000051
224.395 30000056
This must be really simple. But I couldn't find it. I tried a pivot table, but that only allows me to summarise or count etc the fields, while I want them all to be displayed. Any ideas?
To elaborate on the pivot table. I put column 1 as row, column 2 as colum and column 3 in the middle, but that comes out with a lot of empty cells and summarised.
I am not sure on which search terms to look, unconsolidised pivot tables haven't provided an answer.
After some discussions with my collegues, this seemed undoable in excel. So I just created a short script to save each "run" (which is the first column) in a seperate file, from csv:
awk -F, '{print > $1}' rw.txt
I'm implementing a DNS(multicast DNS in fact) in c#.
I just want to know if I must encode my uint/int/ushort/... with the LSB on the left or the MSB on the left. And more globally how I could know this? One of this is standard?
Because I didn't found anything in the IETF description. I found a lot of things(each header field length, position), but I didn't found this.
Thank you!
The answer is in RFC 1035 (2.3.2. Data Transmission Order)
Here is the link: http://www.ietf.org/rfc/rfc1035.txt
And the interesting part
2.3.2. Data Transmission Order
The order of transmission of the header and data described in this
document is resolved to the octet level. Whenever a diagram shows a
group of octets, the order of transmission of those octets is the
normal order in which they are read in English. For example, in the
following diagram, the octets are transmitted in the order they are
numbered.
0 1
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| 1 | 2 |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| 3 | 4 |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| 5 | 6 |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
Whenever an octet represents a numeric quantity, the left most bit in
the diagram is the high order or most significant bit. That is, the
bit labeled 0 is the most significant bit. For example, the following
diagram represents the value 170 (decimal).
0 1 2 3 4 5 6 7
+-+-+-+-+-+-+-+-+
|1 0 1 0 1 0 1 0|
+-+-+-+-+-+-+-+-+
Similarly, whenever a multi-octet field represents a numeric quantity
the left most bit of the whole field is the most significant bit.
When a multi-octet quantity is transmitted the most significant octet
is transmitted first.
Column A "Sales Dates", Column B "=A2-A1" for "Date Diff", Column C "Customer Name", Column D "Item", Column E "Items Ordered Count"
My issue is I have to do a running 30 day total for each customer to see that specific items are not being ordered above "x" number within any 30-day period.
Does anyone have any ideas?
I may not be fully understanding your question, but I don't think you can do what you ask in excel. This might be a situation where a database that can do SQL might come in handy.
The best I can come up with in excel is a Pivot Table, with the customers as rows, dates as columns (group by month), and sum of Items Ordered in the data area. Then conditional format the data area to highlight values > your limit.
Perhaps if you provide some sample data & output I can come up with something more like what you need.
The formula would look something like this:
{=SUM(IF((A$2:A2>=A2-29)*(D$2:D2=D2),E$2:E2,0))}
It should be entered into cell F2 and copied down to the last row of your data. I pasted in a test spreadsheet below so you can see where things go (sorry for the formatting--hopefully it will look better if you paste it into Excel).
IMPORTANT: This is an array formula, so after you type in the formula (and don't type in the braces {} when you do), you must press Ctrl-Shift-Enter instead of just Enter (see this link for more details).
What does the formula do? It does two loops:
First, it loops through all the Sales Dates from the beginning of the log to the current row and checks if each date is between the date of the current row and 29 days earlier (which makes a 30-day window). (By "current row" I mean the row where the formula is located.)
Second, it loops through all the Items from the beginning of the log to the current row and checks if there is a match with the Item of the current row.
For any row where both checks are true (the "*" in the formula does an "and" operation), Items Ordered Count is added to the sum, otherwise zero is added to the sum. So, when it's finished, you have a count for each row of how many orders there were in the past 30 days for that item.
HTH,
-Dan
Sales Dates Date Diff Customer Name Item Items Ordered Count 30-Day Count
1/1/2009 0 dfsadf 11336 70 70
1/2/2009 1 asdfd 10218 121 121
1/3/2009 1 fsdfjkfl 10942 101 101
1/6/2009 3 slkdjflsk 13710 80 80
1/7/2009 1 slkdjls 10480 127 127
1/9/2009 2 sdjjf 11336 143 213
1/11/2009 2 woieuriwe 11501 84 84
1/14/2009 3 owqieyurtn 10191 78 78
1/15/2009 1 weisd 10480 113 240
1/16/2009 1 woieuriwe 12024 133 133
1/17/2009 1 vkcjl 13818 125 125
1/20/2009 3 sdflkj 11336 128 341
1/23/2009 3 jnbkdl 10480 141 381
1/25/2009 2 pqcvnlz 10480 137 518
1/27/2009 2 hwodkjgfh 12878 80 80
1/28/2009 1 zjdnfg;pwlkd 10942 123 224
1/31/2009 3 zlkdjnf;psod 13173 93 93
2/2/2009 2 zlknpdodfg 11336 119 390
2/4/2009 2 zjhdfpwskjh 12004 57 57
2/5/2009 1 asdfd 10218 121 121
2/8/2009 3 fsdfjkfl 10942 101 224
2/11/2009 3 slkdjflsk 13710 80 80
2/14/2009 3 slkdjls 10480 127 405
2/16/2009 2 sdjjf 11336 143 390
2/18/2009 2 woieuriwe 11501 84 84
2/21/2009 3 owqieyurtn 10191 78 78
2/24/2009 3 weisd 10480 113 240
2/25/2009 1 woieuriwe 12024 133 133
2/27/2009 2 vkcjl 13818 125 125
2/28/2009 1 sdflkj 11336 128 390