Hi,
i m Jay working for USDA in Kansas city, KS. i m working on project where i need to upload an excel file which is actually a CSV file with column headers. on upload button click i need to read each row and depending on some perticular value in each row i have to insert that row into 3 different tables(depending on the value) in database.
so i need to check the columns first to see if any of the columns are missing, then i need to read each row and while reading each row i need to check if cofips is 999 and district is 99 then i have to insert that row in one table, if cofips is 999 and district is not 99 then in to another table and if cofips is not 999 and district is not 99 then into a different table ( u can see in below data).
i m using ASP.net as front end and C# as back end and Microsoft enterprise library to connect to Database.
please anyone help me with the sample code ...i have been struck with this for the past 2 days in my work.
below is the sample CSV file which is actually in Excel file. please replay me back to my mail id: [email protected]
crop | type | year | state | cnty | stfips | CRD | cofips | commcode | prac | plnt | plntharv | harv | [lnyld | haryld | yldunit | prod | produnit | 107 | 997 | 1993 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 20000 | | 500 | LBS | 10000000 | LBS | 107 | 997 | 1994 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 17000 | | 559 | LBS | 9500000 | LBS | 107 | 997 | 1995 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 15000 | | 580 | LBS | 8700000 | LBS | 107 | 997 | 1996 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 13000 | | 685 | LBS | 8900000 | LBS | 107 | 997 | 1997 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 13000 | | 769 | LBS | 10000000 | LBS | 107 | 997 | 1998 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 18000 | | 778 | LBS | 14000000 | LBS | 107 | 997 | 1999 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 19000 | | 716 | LBS | 13600000 | LBS | 107 | 997 | 2000 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 17000 | | 794 | LBS | 13500000 | LBS | 107 | 997 | 2001 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 14500 | | 793 | LBS | 11500000 | LBS | 107 | 997 | 2002 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 12000 | | 858 | LBS | 10300000 | LBS | 107 | 997 | 2003 | WA | all | 53 | 99 | 999 | 0 | 997 | | | 12500 | | 816 | LBS | 10200000 | LBS | 107 | 997 | 1993 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1500 | | 533 | LBS | 800000 | LBS | 107 | 997 | 1994 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1500 | | 567 | LBS | 850000 | LBS | 107 | 997 | 1995 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1500 | | 560 | LBS | 840000 | LBS | 107 | 997 | 1996 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1000 | | 750 | LBS | 750000 | LBS | 107 | 997 | 1997 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 900 | | 767 | LBS | 690000 | LBS | 107 | 997 | 1998 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1000 | | 610 | LBS | 610000 | LBS | 107 | 997 | 1999 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1000 | | 630 | LBS | 630000 | LBS | 107 | 997 | 2000 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 1000 | | 700 | LBS | 700000 | LBS | 107 | 997 | 2001 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 700 | | 714 | LBS | 500000 | LBS | 107 | 997 | 2002 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 900 | | 722 | LBS | 650000 | LBS | 107 | 997 | 2003 | WA | all | 53 | 21 | 999 | 0 | 997 | | | 700 | | 786 | LBS | 550000 | LBS | 107 | 997 | 1993 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 4000 | | 625 | LBS | 2500000 | LBS | 107 | 997 | 1994 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 3500 | | 714 | LBS | 2500000 | LBS | 107 | 997 | 1995 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 4300 | | 674 | LBS | 2900000 | LBS | 107 | 997 | 1996 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 4500 | | 733 | LBS | 3300000 | LBS | 107 | 997 | 1997 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 4700 | | 651 | LBS | 3060000 | LBS | 107 | 997 | 1998 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 6000 | | 638 | LBS | 3830000 | LBS | 107 | 997 | 1999 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 5500 | | 655 | LBS | 3600000 | LBS | 107 | 997 | 2000 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 5000 | | 800 | LBS | 4000000 | LBS | 107 | 997 | 2001 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 4500 | | 800 | LBS | 3600000 | LBS | 107 | 997 | 2002 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 3400 | | 838 | LBS | 2850000 | LBS | 107 | 997 | 2003 | WA | all | 53 | 25 | 999 | 0 | 997 | | | 4500 | | 778 | LBS | 3500000 | LBS | 107 | 997 | 1993 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 13000 | | 438 | LBS | 5700000 | LBS | 107 | 997 | 1994 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 10500 | | 490 | LBS | 5150000 | LBS | 107 | 997 | 1995 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 8000 | | 525 | LBS | 4200000 | LBS | 107 | 997 | 1996 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 6300 | | 619 | LBS | 3900000 | LBS | 107 | 997 | 1997 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 5800 | | 828 | LBS | 4800000 | LBS | 107 | 997 | 1998 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 9200 | | 922 | LBS | 8480000 | LBS | 107 | 997 | 1999 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 11000 | | 765 | LBS | 8410000 | LBS | 107 | 997 | 2000 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 10000 | | 810 | LBS | 8100000 | LBS | 107 | 997 | 2001 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 8300 | | 819 | LBS | 6800000 | LBS | 107 | 997 | 2002 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 6400 | | 922 | LBS | 5900000 | LBS | 107 | 997 | 2003 | WA | all | 53 | 71 | 999 | 0 | 997 | | | 6000 | | 892 | LBS | 5350000 | LBS | 107 | 997 | 1993 | WA | all | 53 | 77 | 999 | 0 | 997 | | | 1000 | | 700 | LBS | 700000 | LBS | 107 | 997 | 1994 | WA | all | 53 | 77 | 999 | 0 | 997 | | | 1000 | | 800 | LBS | 800000 | LBS |
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