Corpus composition research
Kanji Pair Research
Enter one kanji to discover other characters recorded in the same JMnedict name spellings, or enter two kanji to inspect that exact co-occurrence. Every count in this research view describes the imported corpus—not population popularity in Japan.
沙
Jōyō · KANJIDIC grade 8 · 7 strokes
弥sand
Jōyō · KANJIDIC grade 8 · 8 strokes
Find exact-kanji names →all the more, increasingly
Recorded names
Name readings containing both characters
The pair only has to occur in the same written form; the two kanji are not required to be adjacent unless counted in the adjacency statistics above.
Given name
沙弥伽
9 source-recorded spellings in this reading group contain both 沙 and 弥Given nameSayaka
さやか
沙亜弥
2 source-recorded spellings in this reading group contain both 沙 and 弥Given nameSāya
さあや
弥沙希
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameMisaki
みさき
阿沙弥
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameAsami
あさみ
弥沙音
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameMisato
みさと
弥沙
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameMisa
みさ
弥沙子
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameMisako
みさこ
沙弥
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameSaya
さや
沙弥子
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameSayako
さやこ
沙弥奈
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameSayana
さやな
沙弥
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameSami
さみ
弥香沙
1 source-recorded spelling in this reading group contain both 沙 and 弥Given nameMikasa
みかさ
沙弥音
1 source-recorded spelling in this reading group contain both 沙 and 弥Sayane
さやね
Evidence boundary
Co-occurrence is not popularity or etymology
The pair relation comes from exact JMnedict source rows through the compact kanji-usage index. KANJIDIC2 contributes character metadata only. A high corpus count can reflect dictionary coverage and should not be read as a national usage frequency.