Lumenworks Csv reader To read columns with same Names Or avoid ` An item with the same key has already been added`

You've stumped me -- I don't know of any CSV parser that accounts for duplicate column headers, and I've tested quite a few of them. There are CSV parsers which will give you raw column data, though, and with some leg work you can use this as a building block to get your data into a friendlier state.

This will return a sequence of Dictionary<string, List<string>>, one for each record, with the key being the header and the list being all the columns with the same header:

using System.IO;
using System.Collections.Generic;
using Ctl.Data;

static IEnumerable<Dictionary<string, List<string>>> ReadCsv(string filePath)
{
    using (StreamReader sr = new StreamReader(filePath))
    {
        CsvReader csv = new CsvReader(sr);

        // first read in the header.

        if (!csv.Read())
        {
            yield break; // an empty file, break out early.
        }

        RowValue header = csv.CurrentRow;

        // now the records.

        while (csv.Read())
        {
            Dictionary<string, List<string>> dict =
                new Dictionary<string, List<string>>(header.Count);

            RowValue record = csv.CurrentRow;

            // map each column to a header value

            for (int i = 0; i < record.Count; ++i)
            {
                // if there are more values in the record than the header,
                // assume an empty string as header.

                string headerValue = (i < header.Count ? header[i].Value : null)
                    ?? string.Empty;

                // get the list, or create if it doesn't exist.

                List<string> list;

                if (!dict.TryGetValue(headerValue, out list))
                {
                    dict[headerValue] = list = new List<string>();
                }

                // finally add column value to the list.

                list.Add(record[i].Value);
            }

            yield return dict;
        }
    }
}

I'm not familiar enough with Lumenworks -- this uses Ctl.Data, which I know will allow for formatted JSON data and any other weirdness within columns so long as it is properly quoted. (disclaimer: I'm the author of Ctl.Data)