How about:
var most = list.GroupBy(i=>i).OrderByDescending(grp=>grp.Count())
.Select(grp=>grp.Key).First();
or in query syntax:
var most = (from i in list
group i by i into grp
orderby grp.Count() descending
select grp.Key).First();
Of course, if you will use this repeatedly, you could add an extension method:
public static T MostCommon<T>(this IEnumerable<T> list)
{
return ... // previous code
}
Then you can use:
var most = list.MostCommon();
Not sure about the lambda expressions, but I would
Sort the list [O(n log n)]
Scan the list [O(n)] finding the longest run-length.
Scan it again [O(n)] reporting each number having that run-length.
This is because there could be more than one most-occurring number.
Taken from my answer here:
public static IEnumerable<T> Mode<T>(this IEnumerable<T> input)
{
var dict = input.ToLookup(x => x);
if (dict.Count == 0)
return Enumerable.Empty<T>();
var maxCount = dict.Max(x => x.Count());
return dict.Where(x => x.Count() == maxCount).Select(x => x.Key);
}
var modes = { }.Mode().ToArray(); //returns { }
var modes = { 1, 2, 3 }.Mode().ToArray(); //returns { 1, 2, 3 }
var modes = { 1, 1, 2, 3 }.Mode().ToArray(); //returns { 1 }
var modes = { 1, 2, 3, 1, 2 }.Mode().ToArray(); //returns { 1, 2 }
I went for a performance test between the above approach and David B's TakeWhile
.
source = { }, iterations = 1000000
mine - 300 ms, David's - 930 mssource = { 1 }, iterations = 1000000
mine - 1070 ms, David's - 1560 mssource = 100+ ints with 2 duplicates, iterations = 10000
mine - 300 ms, David's - 500 mssource = 10000 random ints with about 100+ duplicates, iterations = 1000
mine - 1280 ms, David's - 1400 ms
Here is another answer, which seems to be fast. I think Nawfal's answer is generally faster but this might shade it on long sequences.
public static IEnumerable<T> Mode<T>(
this IEnumerable<T> source,
IEqualityComparer<T> comparer = null)
{
var counts = source.GroupBy(t => t, comparer)
.Select(g => new { g.Key, Count = g.Count() })
.ToList();
if (counts.Count == 0)
{
return Enumerable.Empty<T>();
}
var maxes = new List<int>(5);
int maxCount = 1;
for (var i = 0; i < counts.Count; i++)
{
if (counts[i].Count < maxCount)
{
continue;
}
if (counts[i].Count > maxCount)
{
maxes.Clear();
maxCount = counts[i].Count;
}
maxes.Add(i);
}
return maxes.Select(i => counts[i].Key);
}
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With