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.
央
Jōyō · KANJIDIC grade 3 · 5 strokes
菜center, middle
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
伶央菜
4 source-recorded spellings in this reading group contain both 央 and 菜Given nameReona
れおな
菜央実
3 source-recorded spellings in this reading group contain both 央 and 菜Given nameNaomi
なおみ
理央菜
3 source-recorded spellings in this reading group contain both 央 and 菜Given nameRiona
りおな
伊央菜
2 source-recorded spellings in this reading group contain both 央 and 菜Given nameIona
いおな
菜央子
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameNaoko
なおこ
菜央
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameNao
なお
菜央恵
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameNaoe
なおえ
菜奈央
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameNanao
ななお
未央菜
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameMiona
みおな
詩央菜
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameShiona
しおな
央菜
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameTeruna
てるな
菜央羽
1 source-recorded spelling in this reading group contain both 央 and 菜Given nameNaoha
なおは
藍央菜
1 source-recorded spelling in this reading group contain both 央 and 菜Aiona
あいおな
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.