Converting DataSet/DataTable to CSV

Question

Please let me know, if there any way to generate CSV files from a DataTable or DataSet? To be specific, without manually iterating through rows of DataTable and concatenatin

Answer 1

There is, I hope, also a possible way for doing that:

    static void Main(string[] args)
    {
        DataTable dt = new DataTable("MyTable");
        dt.Columns.Add("Id", typeof(int));
        dt.Columns.Add("Name", typeof(string));
        DataRow dr1 = dt.NewRow();
        dr1["Id"] = 1;
        dr1["Name"] = "John Smith";
        dt.Rows.Add(dr1);
        DataRow dr2 = dt.NewRow();
        dr2["Id"] = 2;
        dr2["Name"] = "John West";
        dt.Rows.Add(dr2);

        List<DataRow> list = dt.AsEnumerable().ToList();
        var strlist = from dr in list
                      select dr[0] + ", " + dr[1];
        var csv = string.Join(Environment.NewLine,strlist);
        Console.WriteLine(csv);
    }

Answer 2

A relative simple, compact and quite flexible solution could be the following extension method:

public static string ToCsv(this DataTable table, string colSep = "", string rowSep = "\r\n")
{
    var format = string.Join(colSep, Enumerable.Range(0, table.Columns.Count)
                                            .Select(i => string.Format("{{{0}}}", i)));

    return string.Join(rowSep, table.Rows.OfType<DataRow>()
                                        .Select(i => string.Format(format, i.ItemArray)));
}

Please note that this solution could cause problems with huge amounts of data, in which case you should stream the output. Quoting and formatting would of course make the code more complex.

Answer 3

There are several ways to do that.

One of the simplest (IMO) is using FileHelpers Library

FileHelpers.CsvEngine.DataTableToCsv(dataTable, filename);

Answer 4

//Dataset To Xls
ExportDataSetToCsvFile(DS,@"C:\\");

internal static void ExportDataSetToCsvFile(DataSet _DataSet, string DestinationCsvDirectory)
{
    try
    {
        foreach (DataTable DDT in _DataSet.Tables)
        {
            String MyFile = @DestinationCsvDirectory + "\\_" + DDT.TableName.ToString() + DateTime.Now.ToString("yyyyMMddhhMMssffff") + ".csv";//+ DateTime.Now.ToString("ddMMyyyyhhMMssffff")
            using (var outputFile = File.CreateText(MyFile))
            {
                String CsvText = string.Empty;

                foreach (DataColumn DC in DDT.Columns)
                {
                    if (CsvText != "")
                        CsvText = CsvText + "," + DC.ColumnName.ToString();
                    else
                        CsvText = DC.ColumnName.ToString();
                }
                outputFile.WriteLine(CsvText.ToString().TrimEnd(','));
                CsvText = string.Empty;

                foreach (DataRow DDR in DDT.Rows)
                {
                    foreach (DataColumn DCC in DDT.Columns)
                    {
                        if (CsvText != "")
                            CsvText = CsvText + "," + DDR[DCC.ColumnName.ToString()].ToString();
                        else
                            CsvText = DDR[DCC.ColumnName.ToString()].ToString();
                    }
                    outputFile.WriteLine(CsvText.ToString().TrimEnd(','));
                    CsvText = string.Empty;
                }
                System.Threading.Thread.Sleep(1000);
            }
        }
    }
    catch (Exception Ex)
    {
        throw Ex;
    }  
}

Answer 5

So this is a fairly bizarre solution, but it works faster than most as it makes use of the JSON.net library's serialization. This speeds the solution up significantly.

Steps:

1. Create array of every column name in the data table, should be simple

2. Use JSON.net to convert datatable to a json string

   string json = JsonConvert.SerializeObject(dt, Formatting.None);

3. Begin making use of the Replace function on c# strings and strip the json string of all json formatting.

   json = json.Replace("\"", "").Replace("},{", "\n").Replace(":", "").Replace("[{", "").Replace("}]", "");

4. Then use the array from step 1 to remove all column names from the json string. You are left with a csv formatted string.

5. Consider using the array created in step 1 to add the column names back in as the first row in csv format.