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.
菜
Jōyō · KANJIDIC grade 4 · 11 strokes
葉vegetable, side dish, greens
Jōyō · KANJIDIC grade 3 · 12 strokes
Find exact-kanji names →leaf, plane, lobe
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
菜の葉
3 source-recorded spellings in this reading group contain both 菜 and 葉Given nameNanoha
なのは
奈菜葉
2 source-recorded spellings in this reading group contain both 菜 and 葉Given nameNanaha
ななは
葉菜
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameHana
はな
葉菜子
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameHanako
はなこ
菜奈葉
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameNanaho
ななほ
葉菜花
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameHanaka
はなか
菜葉子
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameNayoko
なよこ
華菜葉
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameKanaha
かなは
菜津葉
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameNatsuha
なつは
菜葉
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameNakaba
なかば
菜葉
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameNayo
なよ
葉那菜
1 source-recorded spelling in this reading group contain both 菜 and 葉Given nameBanana
ばなな
菜葉菜
1 source-recorded spelling in this reading group contain both 菜 and 葉Nahana
なはな
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.