Why Pivot Tables
Pivot tables summarize large datasets by grouping rows and columns by chosen fields and counting matches. This reveals distributional patterns useful in linguistic analysis (e.g., tone sequences, morphological categories, environments).
What Is This Useful For?
This app helps you quickly summarize Dekereke (or similar) linguistic datasets. A common use is exploring tone patterns by cross-tabulating tone melodies (rows) against syllable templates (columns), or other phonological/morphological categories.
Tone Melodies × Syllable Templates
| Melody \\ Template | CV | CVCV | CVV |
|---|---|---|---|
| H | 12 | 8 | 5 |
| L | 9 | 11 | 4 |
| HL | 7 | 13 | 6 |
| LH | 10 | 6 | 3 |
Click a cell in the PWA to see and copy the exact record references for that count.
Part of Speech × Tone Category
| POS \\ Tone | H | L | HL | LH |
|---|---|---|---|---|
| Noun | 21 | 14 | 5 | 3 |
| Verb | 8 | 17 | 9 | 4 |
| Adj | 6 | 5 | 2 | 1 |
Suggested Reading
For background and practical guidance, see Chapter 2 of Keith Snider’s work:
Snider, K. (2014). Tone Analysis for Field Linguists (2nd ed.). Dallas, TX: SIL International. Chapter 2.
APA reference: Snider, K. (2014). Tone Analysis for Field Linguists (2nd ed.). Dallas, TX: SIL International.