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.
江
Jōyō · KANJIDIC grade 8 · 6 strokes
菜creek, inlet, bay
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
江利菜
5 source-recorded spellings in this reading group contain both 江 and 菜Given nameErina
えりな
佳菜江
4 source-recorded spellings in this reading group contain both 江 and 菜Given nameKanae
かなえ
佐菜江
3 source-recorded spellings in this reading group contain both 江 and 菜Given nameSanae
さなえ
奈菜江
3 source-recorded spellings in this reading group contain both 江 and 菜Given nameNanae
ななえ
三菜江
3 source-recorded spellings in this reading group contain both 江 and 菜Given nameMinae
みなえ
江菜
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameEna
えな
菜美江
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameNamie
なみえ
江巳菜
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameEmina
えみな
菜江
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameNae
なえ
江菜子
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameEnako
えなこ
日菜江
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameHinae
ひなえ
江菜美
1 source-recorded spelling in this reading group contain both 江 and 菜Given nameEnami
えなみ
優江菜
1 source-recorded spelling in this reading group contain both 江 and 菜Yuena
ゆえな
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.