Count the words that matter
A support tool skims ticket text to see which terms keep coming up, ignoring the little joining words.
- Split on whitespace and compare in lowercase.
- Words shorter than three characters are noise and are left out.
- The result maps each remaining word to how many times it appeared.
WordFrequency(text: string) → map<string, int>
C# needs a compiler and Drill does not host one yet, so this page is the reference rather than an exercise: the problem, worked examples, and the solution in full. To type it out, the same problem runs in Python.
Where you start
public Dictionary<string, int> WordFrequency(string text) {
}Worked examples
| Call | Result |
|---|---|
WordFrequency("card declined card") | new Dictionary<string, int> { { "card", 2 }, { "declined", 1 } } |
WordFrequency("The the THE") | new Dictionary<string, int> { { "the", 3 } } |
WordFrequency("a an I ok") | new Dictionary<string, int> { } |
WordFrequency("") | new Dictionary<string, int> { } |
Hint
Lowercase before counting, or "Payment" and "payment" end up as two entries.
Reference solution in C#
public Dictionary<string, int> WordFrequency(string text) {
var result = new Dictionary<string, int>();
foreach (var w in text.ToLowerInvariant().Split((char[]) null, StringSplitOptions.RemoveEmptyEntries)) {
if (w.Length < 3) continue;
result[w] = result.ContainsKey(w) ? result[w] + 1 : 1;
}
return result;
}