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.
都
Jinmeiyō · KANJIDIC grade 10 · 11 strokes
紗capital, metropolis
Jinmeiyō · KANJIDIC grade 9 · 10 strokes
Find exact-kanji names →gauze, gossamer
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
千紗都
3 source-recorded spellings in this reading group contain both 都 and 紗Given nameChisato
ちさと
紗都実
2 source-recorded spellings in this reading group contain both 都 and 紗Given nameSatomi
さとみ
未紗都
2 source-recorded spellings in this reading group contain both 都 and 紗Given nameMisato
みさと
紗都花
2 source-recorded spellings in this reading group contain both 都 and 紗Given nameSatoka
さとか
紗都子
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameSatoko
さとこ
紗都貴
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameSatsuki
さつき
都香紗
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameTsukasa
つかさ
紗都里
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameSatori
さとり
紗都
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameSato
さと
都羽紗
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameTsubasa
つばさ
梨紗都
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameRisato
りさと
紗都音
1 source-recorded spelling in this reading group contain both 都 and 紗Given nameSatone
さとね
都萌紗
1 source-recorded spelling in this reading group contain both 都 and 紗Tomosa
ともさ
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.