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.
万
Jōyō · KANJIDIC grade 2 · 3 strokes
喜ten thousand, 10,000
Jōyō · KANJIDIC grade 5 · 12 strokes
Find exact-kanji names →rejoice, take pleasure in
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
万喜夫
3 source-recorded spellings in this reading group contain both 万 and 喜Given nameMakio
まきお
万喜
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMaki
まき
万喜子
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMakiko
まきこ
万喜
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameKazuki
かずき
他万喜
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameTamaki
たまき
万喜枝
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMakie
まきえ
万喜乃
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMakino
まきの
千万喜
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameChimaki
ちまき
万喜彦
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMakihiko
まきひこ
万喜紫
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMakishi
まきし
万寿喜
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMasuyoshi
ますよし
万喜多
1 source-recorded spelling in this reading group contain both 万 and 喜Given nameMakita
まきた
万喜三
1 source-recorded spelling in this reading group contain both 万 and 喜Makizō
まきぞう
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.