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.
樹
Jōyō · KANJIDIC grade 6 · 16 strokes
菜timber, trees, wood
Jōyō · KANJIDIC grade 4 · 11 strokes
Find exact-kanji names →vegetable, side dish, greens
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
亜樹菜
4 source-recorded spellings in this reading group contain both 樹 and 菜Given nameAkina
あきな
樹梨菜
2 source-recorded spellings in this reading group contain both 樹 and 菜Given nameJurina
じゅりな
優樹菜
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameYukina
ゆきな
菜津樹
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameNatsuki
なつき
菜樹子
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameNanako
ななこ
樹菜
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameJuna
じゅな
樹菜
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameMikina
みきな
実菜樹
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameMinaki
みなき
樹菜子
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameKinako
きなこ
樹菜里
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameKinari
きなり
菜樹
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameNaki
なき
想菜樹
1 source-recorded spelling in this reading group contain both 樹 and 菜Given nameSonata
そなた
菜樹
1 source-recorded spelling in this reading group contain both 樹 and 菜Naju
なじゅ
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.