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.
紗
Jinmeiyō · KANJIDIC grade 9 · 10 strokes
菜gauze, gossamer
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
亜紗菜
3 source-recorded spellings in this reading group contain both 紗 and 菜Given nameAsana
あさな
紗菜恵
3 source-recorded spellings in this reading group contain both 紗 and 菜Given nameSanae
さなえ
紗也菜
3 source-recorded spellings in this reading group contain both 紗 and 菜Given nameSayana
さやな
紗梨菜
2 source-recorded spellings in this reading group contain both 紗 and 菜Given nameSarina
さりな
紗菜
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameSena
せな
紗菜
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameSana
さな
紗菜
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameSuzuna
すずな
紗菜子
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameSanako
さなこ
菜紗
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameNasa
なさ
紗知菜
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameSachina
さちな
紗菜
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameShana
しゃな
菜紗子
1 source-recorded spelling in this reading group contain both 紗 and 菜Given nameNasako
なさこ
紗和菜
1 source-recorded spelling in this reading group contain both 紗 and 菜Sawana
さわな
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.