What is causing a csv load error in weka? - csv
Im receiving the following error when trying to open a CSV file in Weka version 3.8.5
File not recognized as an 'CSV data files' file Reason: wrong number
of values. Read 2, expected 12, read Token [EOL], Line 2 Problem
encountered on Line:2
I have read solutions to similar errors on this site and can't seem to find what is wrong with my particular file. However, as a very newbie weka user, it may just be my misunderstanding of the issue. Can someone take a look at the sample csv data below and let me know if you see what I am not understnding or missing?
LossMonth,LossYear,ClaimNumber,PolicyNumber,ClaimBranch,Agency,LocationCounty,CATCode,CauseCode,IncurredLoss,CurrentReserves,"
City",State,ZIPCODE,"
COLLISIONTYPECD","
CLOSEDDT",DaystoCLose,"
FATALITYCNT","
FATALITYIND","
FAULTRATINGIND","
AUTOGLASSIND","
DEERLOSSIND","
WEATHERRELATEDIND","
POLICYTIERCD",ClaimStatus,AgencyHandled,VEHICLEYEAR,DRIVERRELATIONTOINSUREDDESC,TOTALLOSSIND,INSURANCESCORE,Age
10,2016,4125858,20169200,4,113,73,1,comp,2525,0,PADUCAH,KY,42001,x,42692,18,0,0,0,0,0,1,70,1,0,2004,Other third party,0,703,73
1,2018,4265645,20137828,13,106,37,1,hail,3164,0,BAGDAD,KY,40003,x,43214,88,0,0,0,0,0,0,50,1,0,2010,Named Insured,1,799,63
12,2016,4136759,20322058,5,105,105,1,hail,2547,0,GEORGETOWN,KY,40324,x,42713,2,0,0,0,0,0,0,10,1,0,2010,Named Insured,0,999,68
1,2016,4033032,20175699,13,106,106,1,comp,15327,0,SIMPSONVILLE,KY,40067,x,42469,73,0,0,0,0,0,1,80,1,0,2000,Named Insured,1,999,34
9,2016,4116782,20133146,2,115,115,1,wind,7529,0,SPRINGFIELD,KY,40069,x,42649,8,0,0,0,0,0,0,10,1,0,2003,Named Insured,0,783,47
2,2016,4038442,20170355,7,148,10,1,hail,3631,0,ASHLAND,KY,41101,x,42417,1,0,0,0,0,0,0,50,1,0,2010,Named Insured,0,778,42
2,2016,4039439,20218265,7,45,10,1,hail,3579,0,FLATWOODS,KY,41139,x,42444,25,0,0,0,0,0,0,40,1,0,2013,Named Insured,0,820,52
2,2016,4039440,20218265,7,45,10,1,hail,570,0,FLATWOODS,KY,41139,x,42422,3,0,0,0,0,0,0,40,1,0,2012,Named Insured,0,820,52
3,2018,4275810,20126522,15,40,40,1,hail,3747,0,LANCASTER,KY,40444,x,43216,55,0,0,0,0,0,0,10,1,0,2009,Named Insured,1,999,74
5,2016,4071936,20461965,15,40,40,1,hail,525,0,LANCASTER,KY,40444,x,42521,7,0,0,0,0,0,0,50,1,0,2006,Named Insured,0,999,68
3,2016,4046685,20226270,7,35,35,1,hail,3558,0,FLEMINGSBURG,KY,41041,x,42447,2,0,0,0,0,0,0,80,1,0,2012,Named Insured,0,842,69
4,2016,4055942,20439287,7,35,35,1,hail,2551,0,EWING,KY,41039,x,42475,1,0,0,0,0,0,0,70,1,0,2006,Named Insured,0,867,48
1,2016,4026514,20394097,7,148,10,1,hail,1350,0,ASHLAND,KY,41101,x,42376,3,0,0,0,0,0,0,40,1,0,2007,Named Insured,0,637,65
3,2016,4047152,20212062,15,141,76,1,hail,1739,0,BEREA,KY,40403,x,42473,27,0,0,0,0,0,0,80,1,0,2008,Named Insured,0,777,77
2,2016,4035512,20103029,15,40,40,1,hail,2008,0,LANCASTER,KY,40444,x,42405,1,0,0,0,0,0,0,0,1,0,2000,Named Insured,1,885,72
1,2016,4030456,20385643,15,120,40,1,hail,1497,0,LANCASTER,KY,40444,x,42450,62,0,0,0,0,0,0,20,1,0,2013,Named Insured,0,839,65
4,2016,4053299,20251610,5,69,11,1,hail,1535,0,DANVILLE,KY,40422,x,42514,48,0,0,0,0,0,0,100,1,0,2013,Insured,0,999,64
6,2016,4076264,20337992,17,140,1,1,hail,1799,0,MILLTOWN,KY,42728,x,42529,2,0,0,0,0,0,0,50,1,0,2002,Named Insured,0,999,84
8,2017,4217498,20596983,8,86,86,1,hail,660,0,TOMPKINSVILLE,KY,42167,x,42954,0,0,0,0,0,0,0,100,1,0,2012,Named Insured,0,999,45
1,2016,4026053,20511114,4,113,113,1,hail,1310,0,STURGIS,KY,42459,x,42376,3,0,0,0,0,0,0,100,1,0,2003,Named Insured,0,694,44
1,2016,4026766,20656586,4,113,113,1,hail,2360,0,MORGANFIELD,KY,42437,x,42383,9,0,0,0,0,0,0,20,1,0,2010,Named Insured,0,999,89
1,2016,4027473,20085251,6,42,42,1,hail,1699,0,MAYFIELD,KY,42066,x,42381,5,0,0,0,0,0,0,90,1,0,2008,Named Insured,0,747,50
1,2016,4029284,20167051,17,109,109,1,wind,3133,0,CAMPBELLSVILLE,KY,42718,x,42387,5,0,0,0,0,0,0,10,1,0,1993,Named Insured,0,886,78
1,2016,4031937,20326278,3,81,12,1,comp,3385,0,FOSTER,KY,41043,x,42402,8,0,0,0,0,0,1,40,1,0,2003,Named Insured,0,723,79
1,2016,4027931,20339366,8,107,107,1,wind,5858,0,FRANKLIN,KY,42134,x,42447,70,0,0,0,0,0,0,20,1,0,2014,Named Insured,0,940,80
1,2016,4028456,20453076,15,87,87,1,comp,2056,0,JEFFERSONVILLE,KY,40337,x,42387,7,0,0,0,0,0,1,100,1,0,2013,Named Insured,0,999,51
1,2016,4028597,20051661,4,113,113,1,hail,5320,0,WAVERLY,KY,42462,x,42712,332,0,0,0,0,0,0,20,1,0,2014,Named Insured,0,717,58
3,2016,4046687,20018268,6,42,42,1,hail,2736,0,MAYFIELD,KY,42066,x,42450,5,0,0,0,0,0,0,110,1,0,2012,Named Insured,0,735,73
9,2016,4116499,20128172,3,96,59,1,glss,320,0,TAYLOR MILL,KY,41015,x,42660,20,0,0,0,0,0,1,0,1,0,1997,Spouse,0,923,81
1,2016,4026247,20086164,4,113,113,1,hail,1611,0,MORGANFIELD,KY,42437,x,42376,3,0,0,0,0,0,0,10,1,0,2013,Named Insured,0,902,61
1,2016,4027222,20033936,6,79,79,1,glss,105,0,CALVERT CITY,KY,42029,x,42389,14,0,0,0,0,0,1,110,1,0,2001,Named Insured,0,772,57
1,2016,4028311,20059964,4,75,75,1,comp,1040,0,SACRAMENTO,KY,42372,x,42382,2,0,0,0,0,0,1,10,1,0,1996,Named Insured,0,999,64
1,2016,4029164,20541039,6,42,42,1,wind,1495,0,SEDALIA,KY,42079,x,42382,0,0,0,0,0,0,0,0,1,0,2008,Named Insured,0,756,67
1,2016,4027475,20085251,6,42,42,1,hail,940,0,MAYFIELD,KY,42066,x,42381,5,0,0,0,0,0,0,90,1,0,2013,Named Insured,0,747,50
1,2016,4030356,20007300,4,117,117,1,hail,6550,0,DIXON,KY,42409,x,42436,49,0,0,0,0,0,0,40,1,0,2009,Named Insured,0,864,34
Weka's CSVLoader cannot handle rows that span multiple lines (despite quoting). Once all your rows (header and data) are one per line, you should be fine.
The common-csv (unofficial) Weka package should be able to handle rows spanning multiple lines.
Related
Read a log file in R
I'm trying to read a log file in R.
It looks like an extract from a JSON file to me, but when trying to read it using jsonlite I get the following error message: "Error: parse error: trailing garbage".
Here is how my log file look like:
{"date":"2017-05-11T04:37:15.587Z","userId":"admin","module":"Quote","action":"CreateQuote","identifier":"-.admin1002"},
{"date":"2017-05-11T05:12:24.939Z","userId":"a145fhyy","module":"Quote","action":"Call","identifier":"RunUY"},
{"date":"2017-05-11T05:12:28.174Z","userId":"a145fhyy","license":"named","usage":"External","module":"Catalog","action":"OpenCatalog","identifier":"wks.klu"},
Has you can see, the column name is precised directly in front of the content for each line (e.g: "date": or "action":)
And some line can skip some columns and add some other.
What I want to get as output would be to have 7 columns with the corresponding data filled in each:
date
userId
license
usage
module
action
identifier
Does anyone has a suggestion about how to get there?
Thanks a lot in advance
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Thanks everyone for your answers. Here are some precisions about my issue:
The data that I gave as example in an extract of one of my log files. I've got a lot of them that I need to read as one unique table.
I haven't added any commas or anything to it.
#r2evans
I've tried the following:
Log3 <-read.table("/Projects/data/analytics.log.agregated.2017-05-11.log") jsonlite::stream_in(textConnection(gsub(",$","",Log3)))
It returns the following error:
Error: lexical error: invalid char in json text.
c(17, 18, 19, 20, 21, 22, 23, 2
(right here) ------^
I'm not sure how to use sed -e 's/,$//g' infile > outfile and Sys.which("sed"), that something I'm not familiar with. I'm looking into it, but if you have anymore precisions to give me about the usage of it that would be great.
I have saved your example as a file "test.json" and was able to read and parse it like this:
library(jsonlite)
rf <- read_file("test.json")
rfr <- gsub("\\},", "\\}", rf)
data <- stream_in(textConnection(rfr))
It parses and simplifies into a neat data frame exactly like you want. What I do is look for "}," rather than ",$", because the very last comma is not (necessarily) followed by a newline character(s).
However, this might not be the best solution for very large files.. For those you may need to first look for a way to modify the text file itself by getting rid of the commas. Or, if that's possible, ask the people who exported this file to export it in a normal ndjson format:-)
Premature end of line Weka error
I'm new to Weka and I have to use it for a University project. So, I created a .csv file and when I try to upload it to Weka, it says: "not recognised as a CSV data file. Reason: 1 problem encountered on line 2". Then, if I open the .csv file with Notepad and then save as .arff file, when I try to open it again with Weka, in this case I get another error message: "not recognised as an arff data file. Reason: premature end of line, read Token[EOL], line 8". Please help, I don't know much about working with Weka and really don't know what could be the problem, even though I did a lot of research about this problem. This is the file: https://app.box.com/s/adfpf1zatgpl5mo20u5hdd1gnqihnq40 #Relation "PIB_Rata inflatiei" #Attribute "PIB" NUMERIC #Attribute "Rata_inflatiei" NUMERIC #Data 30624.3,20780.9,27980.4,31920.3,37657.0,37168.3,35838.9,41978.0,36183.4,37439.0,40717.1,46174.0,59867.6,76217.6,99699.2,123533.7,171540.2,208185.1,167421.6,167998.1,185362.3,171664.6,191548.1,199325.9,177956.0 128.0,211.2,255.2,136.8,32.2,38.8,154.8,59.1,45.8,45.7,34.5,22.5,15.3,11.3,9.0,6.6,4.8,7.8,5.6,6.1,5.8,3.3,4.0,1.1,-0.6
In the ARFF format (as well as CSV) instances are rows, and attributes are columns. Your file thus has too many columns, ever row must have exactly.two values.
Golang CSV read : extraneous " in field error
I am using a simple program to read CSV file, somehow I noticed when I created a CSV using EXCEL or windows based computer go library fails to read it. even when I use cat command it only shows me last line on the terminal. It always results in this error extraneous " in field. I researched somewhat than I found it is somewhat related to carriage return differences between OS. But I really want to ask how to make a generic csv reader. I tried reading the same csv using pandas and it was reading successfully. But i am not been able to achieve this using my Go code. Also screen shot of correct csv Is here
Your file clearly shows that you've got an extra quote at the end of the content. While programs like pandas may be fine with that, I assume it's not valid csv so go does return an error. Quick example of what's wrong with your data: https://play.golang.org/p/KBikSc1nzD Update: After your update and a little bit of searching, I have to apoligize, the carriage return does matter and seems to be tha main culprit here, Go seems to be ok handling the \r\n windows variant but not the \r one. In that case what you can do is wrap the bytes.Reader into a custom reader that replaces the \r byte with the \n byte. Here's an example: https://play.golang.org/p/vNjzwAHmtg Please note, that the example is just that, an example, it's not handling all the possible cases where \r might be a legit byte.
Java.io.IOException: wrong number of values (WEKA CSV to ARFF)
Currently working on a Data Mining project using my own dataset I had found using Weka. The only issue is that taking my file from csv format and converting it into arff format is causing issues. java.io.IOException: wrong number of values. Read 2, expected 5, Read Token[EOL], line 3 This is the error I am getting. I have browsed around online looking for similar issues and have tried removing all quotes and special characters that throw this exception. Every place I looked told me to remove special characters and I believe there are none left. The link to my dataset is here : https://docs.google.com/spreadsheets/d/1xqEe7MZE9SdKB_yvFSgWeSVYuDrq0b31Eu5oECNbGH0/edit#gid=1736568367&vpid=A1 This is the first three lines of my file where the first is the attribute names, file is separated by commas in note Inequality Adjusted HPI Rank,Sub Region,Inequality Adjusted Life Expectancy,Inquality Adjusted Well being,Footprint ,Inequality adjusted HPI 1,1,73.1,6.9,2.5,48.2 2,6,65.17333333,5.487667631,1.390974448,45.97489063
If you open your file with a text editor, you will see that Footprint has quotes around it. Delete the quotes and you are good to go!
Weka is normally not that good in reading CSV files that include special characters, and ARFF files are normally easier to use. Therefore, in such cases, the easiest way is to convert your CSV file to an ARFF file using R ("RWeka" and "foreign" libraries can handle this conversion).
There is also another possibility. I was creating my CSV file and the header had a different number of elements compared to the rest of the data. So, check the header as well...!
Trouble following Encrypted Big-Query tutorial document
I wanted to try out the encrypted big query client for google big query and I've been having some trouble.
I'm following the instructions outlined in this PDF:
https://docs.google.com/file/d/0B-WB8hYCrhZ6cmxfWFpBci1lOVE/edit
I get to the point where I'm running this command:
ebq load --master_key_filename="key_file" testdataset.cars cars.csv cars.schema
And I'm getting an error string which ends with:
raise ValueError("No JSON object could be decoded")
I've tried a few different formats for my .csv and .schema files but none have worked. Here are my latest versions.
cars.schema:
[{"name": "Year", "type": "integer", "mode": "required", "encrypt": "none"}
{"name": "Make", "type": "string", "mode": "required", "encrypt": "pseudonym"}
{"name": "Model", "type": "string", "mode": "required", "encrypt": "probabilistic_searchwords"}
{"name": "Description", "type": "string", "mode": "nullable", "encrypt": "searchwords"}
{"name": "Website", "type": "string", "mode": "nullable", "encrypt": "searchwords","searchwords_separator": "/"}
{"name": "Price", "type": "float", "mode": "required", "encrypt": "probabilistic"}
{"name": "Invoice_Price", "type": "integer", "mode": "required", "encrypt": "homomorphic"}
{"name": "Holdback_Percentage", "type": "float", "mode": "required", "encrypt":"homomorphic"}]
cars.csv:
1997,Ford,E350, "ac\xc4a\x87, abs, moon","www.ford.com",3000.00,2000,1.2
1999,Chevy,"Venture ""Extended Edition""","","www.cheverolet.com",4900.00,3800,2.3
1999,Chevy,"Venture ""Extended Edition, Very Large""","","www.chevrolet.com",5000.00,4300,1.9
1996,Jeep,Grand Cherokee,"MUST SELL! air, moon roof,loaded","www.chrysler.com/jeep/grandcherokee",4799.00,3950,2.4
I believe the issue may be that you need to move the --master_key_filename argument before the load argument. If that doesn't work, can you send the output of adding --apilog=- as the first argument? Also, there is an example script file of running ebq here: https://code.google.com/p/bigquery-e2e/source/browse/#git%2Fsamples%2Fch13