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  • Labeler: How To: I have a column in a text file with cells that contain both alpha and numeric values in it, but Labeler only sees the cells in that column that are all numeric.
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Labeler: How To: I have a column in a text file with cells that contain both alpha and numeric values in it, but Labeler only sees the cells in that column that are all numeric.

Internal User
2017-04-10
in Version 7

If you look at the txt file example below, it contains the ""CC"" values, but in only a few of the rows, while the remaining rows contain pure numeric values. For example, the data may look like this:

CC8590
CC98292
CC94594
CC94048
CC8576
94647
97253
97697
97908
98213
98214 

The database engine that Labeler is using to interpret the data type for the entire column thinks that the column's data type should be a number, rather than a string. Therefore, since it cannot convert strings beginning with ""CC"" into a number, then it doesn't show the data at all. To learn more about the solution to the problem, see the Labeler's Help topic on ""Schema.ini"". (This is good info to read in any case - to learn more about how Labeler uses TXT files as External Data Sources.) 

Simply setup your Schema.ini file, located in the directory your txt file is in, to look like the example we have below. You might have to re-map text and/or Barcode objects to the appropriate Columns due to the fact that the Column Names might have been changed given the way you created the Schema.ini file and named the columns within. 

Schema.ini Example: 

[Your text file.txt] 
ColNameHeader=True 
Format=CSVDelimited 
MaxScanRows=0 
CharacterSet=OEM 
Col1=Claim text 
Col2=RO text 
Col3=Part text 
Col4=ShipTo text 

If you have a .csv file, use the following schema as your guide:

[LABELMASTER.csv]
ColNameHeader=true
Format=CSVDelimited
MaxScanRows=0
CharacterSet=OEM
Col1="Part Number" char
Col2="Description" char
Col3="Bar Code" char


Notice that the columns are named and their type is declared by the text or char; Labeler will treat that column as text only. It will not affect those columns with numbers only. 

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