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.
衣
Jōyō · KANJIDIC grade 4 · 6 strokes
万garment, clothes, dressing
Jōyō · KANJIDIC grade 2 · 3 strokes
Find exact-kanji names →ten thousand, 10,000
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
万利衣
4 source-recorded spellings in this reading group contain both 衣 and 万Given nameMarie
まりえ
万衣加
3 source-recorded spellings in this reading group contain both 衣 and 万Given nameMaika
まいか
万衣子
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMaiko
まいこ
万衣
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMai
まい
万由衣
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMayuki
まゆき
衣万
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameEma
えま
衣万子
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameImako
いまこ
衣万里
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameImari
いまり
万衣菜
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMaina
まいな
万美衣
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMamī
まみい
万亜衣
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMāi
まあい
万衣乃
1 source-recorded spelling in this reading group contain both 衣 and 万Given nameMaino
まいの
万衣早
1 source-recorded spelling in this reading group contain both 衣 and 万Maisa
まいさ
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.