Pivot data using LINQ

Question

I am trying to see if I can use LINQ to solve a problem I am having. I have a collection of items that contain an Enum (TypeCode) and a User object, and I need to flatten it out to show in a grid. It's hard to explain, so let me show a quick example.

Collection has items like so:

TypeCode | User 
---------------
1        | Don Smith  
1        | Mike Jones  
1        | James Ray  
2        | Tom Rizzo  
2        | Alex Homes  
3        | Andy Bates  

I need the output to be:

1          | 2          | 3  
Don Smith  | Tom Rizzo  | Andy Bates  
Mike Jones | Alex Homes |  
James Ray  |            |  

Thanks to anyone who can help me! I've tried doing this using foreach, but I can't do it that way because I'd be inserting new items to the collection in the foreach, causing an error.

Answer 1

I'm not saying it is a great way to pivot - but it is a pivot...

    // sample data
    var data = new[] {
        new { Foo = 1, Bar = "Don Smith"},
        new { Foo = 1, Bar = "Mike Jones"},
        new { Foo = 1, Bar = "James Ray"},
        new { Foo = 2, Bar = "Tom Rizzo"},
        new { Foo = 2, Bar = "Alex Homes"},
        new { Foo = 3, Bar = "Andy Bates"},
    };
    // group into columns, and select the rows per column
    var grps = from d in data
              group d by d.Foo
              into grp
              select new {
                  Foo = grp.Key,
                  Bars = grp.Select(d2 => d2.Bar).ToArray()
              };

    // find the total number of (data) rows
    int rows = grps.Max(grp => grp.Bars.Length);

    // output columns
    foreach (var grp in grps) {
        Console.Write(grp.Foo + "\t");
    }
    Console.WriteLine();
    // output data
    for (int i = 0; i < rows; i++) {
        foreach (var grp in grps) {
            Console.Write((i < grp.Bars.Length ? grp.Bars[i] : null) + "\t");
        }
        Console.WriteLine();
    }

Answer 2

Marc's answer gives sparse matrix that can't be pumped into Grid directly.
I tried to expand the code from the link provided by Vasu as below:

public static Dictionary<TKey1, Dictionary<TKey2, TValue>> Pivot3<TSource, TKey1, TKey2, TValue>(
    this IEnumerable<TSource> source
    , Func<TSource, TKey1> key1Selector
    , Func<TSource, TKey2> key2Selector
    , Func<IEnumerable<TSource>, TValue> aggregate)
{
    return source.GroupBy(key1Selector).Select(
        x => new
        {
            X = x.Key,
            Y = source.GroupBy(key2Selector).Select(
                z => new
                {
                    Z = z.Key,
                    V = aggregate(from item in source
                                  where key1Selector(item).Equals(x.Key)
                                  && key2Selector(item).Equals(z.Key)
                                  select item
                    )

                }
            ).ToDictionary(e => e.Z, o => o.V)
        }
    ).ToDictionary(e => e.X, o => o.Y);
} 
internal class Employee
{
    public string Name { get; set; }
    public string Department { get; set; }
    public string Function { get; set; }
    public decimal Salary { get; set; }
}
public void TestLinqExtenions()
{
    var l = new List<Employee>() {
    new Employee() { Name = "Fons", Department = "R&D", Function = "Trainer", Salary = 2000 },
    new Employee() { Name = "Jim", Department = "R&D", Function = "Trainer", Salary = 3000 },
    new Employee() { Name = "Ellen", Department = "Dev", Function = "Developer", Salary = 4000 },
    new Employee() { Name = "Mike", Department = "Dev", Function = "Consultant", Salary = 5000 },
    new Employee() { Name = "Jack", Department = "R&D", Function = "Developer", Salary = 6000 },
    new Employee() { Name = "Demy", Department = "Dev", Function = "Consultant", Salary = 2000 }};

    var result5 = l.Pivot3(emp => emp.Department, emp2 => emp2.Function, lst => lst.Sum(emp => emp.Salary));
    var result6 = l.Pivot3(emp => emp.Function, emp2 => emp2.Department, lst => lst.Count());
}

* can't say anything about the performance though.

Answer 3

You can use Linq's .ToLookup to group in the manner you are looking for.

var lookup = data.ToLookup(d => d.TypeCode, d => d.User);

Then it's a matter of putting it into a form that your consumer can make sense of. For instance:

//Warning: untested code
var enumerators = lookup.Select(g => g.GetEnumerator()).ToList();
int columns = enumerators.Count;
while(columns > 0)
{
  for(int i = 0; i < enumerators.Count; ++i)
  {
    var enumerator = enumerators[i];
    if(enumator == null) continue;
    if(!enumerator.MoveNext())
    { 
      --columns;
      enumerators[i] = null;
    }
  }
  yield return enumerators.Select(e => (e != null) ? e.Current : null);
}

Put that in an IEnumerable<> method and it will (probably) return a collection (rows) of collections (column) of User where a null is put in a column that has no data.

Answer 4

I guess this is similar to Marc's answer, but I'll post it since I spent some time working on it. The results are separated by " | " as in your example. It also uses the IGrouping<int, string> type returned from the LINQ query when using a group by instead of constructing a new anonymous type. This is tested, working code.

var Items = new[] {
    new { TypeCode = 1, UserName = "Don Smith"},
    new { TypeCode = 1, UserName = "Mike Jones"},
    new { TypeCode = 1, UserName = "James Ray"},
    new { TypeCode = 2, UserName = "Tom Rizzo"},
    new { TypeCode = 2, UserName = "Alex Homes"},
    new { TypeCode = 3, UserName = "Andy Bates"}
};
var Columns = from i in Items
              group i.UserName by i.TypeCode;
Dictionary<int, List<string>> Rows = new Dictionary<int, List<string>>();
int RowCount = Columns.Max(g => g.Count());
for (int i = 0; i <= RowCount; i++) // Row 0 is the header row.
{
    Rows.Add(i, new List<string>());
}
int RowIndex;
foreach (IGrouping<int, string> c in Columns)
{
    Rows[0].Add(c.Key.ToString());
    RowIndex = 1;
    foreach (string user in c)
    {
        Rows[RowIndex].Add(user);
        RowIndex++;
    }
    for (int r = RowIndex; r <= Columns.Count(); r++)
    {
        Rows[r].Add(string.Empty);
    }
}
foreach (List<string> row in Rows.Values)
{
    Console.WriteLine(row.Aggregate((current, next) => current + " | " + next));
}
Console.ReadLine();

I also tested it with this input:

var Items = new[] {
    new { TypeCode = 1, UserName = "Don Smith"},
    new { TypeCode = 3, UserName = "Mike Jones"},
    new { TypeCode = 3, UserName = "James Ray"},
    new { TypeCode = 2, UserName = "Tom Rizzo"},
    new { TypeCode = 2, UserName = "Alex Homes"},
    new { TypeCode = 3, UserName = "Andy Bates"}
};

Which produced the following results showing that the first column doesn't need to contain the longest list. You could use OrderBy to get the columns ordered by TypeCode if needed.

1         | 3          | 2
Don Smith | Mike Jones | Tom Rizzo
          | James Ray  | Alex Homes
          | Andy Bates | 

Answer 5

@Sanjaya.Tio I was intrigued by your answer and created this adaptation which minimizes keySelector execution. (untested)

public static Dictionary<TKey1, Dictionary<TKey2, TValue>> Pivot3<TSource, TKey1, TKey2, TValue>(
    this IEnumerable<TSource> source
    , Func<TSource, TKey1> key1Selector
    , Func<TSource, TKey2> key2Selector
    , Func<IEnumerable<TSource>, TValue> aggregate)
{
  var lookup = source.ToLookup(x => new {Key1 = keySelector1(x), Key2 = keySelector2(x)});

  List<TKey1> key1s = lookup.Select(g => g.Key.Key1).Distinct().ToList();
  List<TKey2> key2s = lookup.Select(g => g.Key.Key2).Distinct().ToList();

  var resultQuery =
    from key1 in key1s
    from key2 in key2s
    let lookupKey = new {Key1 = key1, Key2 = key2}
    let g = lookup[lookupKey]
    let resultValue = g.Any() ? aggregate(g) : default(TValue)
    select new {Key1 = key1, Key2 = key2, ResultValue = resultValue};

  Dictionary<TKey1, Dictionary<TKey2, TValue>> result = new Dictionary<TKey1, Dictionary<TKey2, TValue>>();
  foreach(var resultItem in resultQuery)
  {
    TKey1 key1 = resultItem.Key1;
    TKey2 key2 = resultItem.Key2;
    TValue resultValue = resultItem.ResultValue;

    if (!result.ContainsKey(key1))
    {
      result[key1] = new Dictionary<TKey2, TValue>();
    }
    var subDictionary = result[key1];
    subDictionary[key2] = resultValue; 
  }
  return result;
}