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.

衣

Jōyō · KANJIDIC grade 4 · 6 strokes

garment, clothes, dressing

羅

Jōyō · KANJIDIC grade 8 · 19 strokes

gauze, thin silk, Rome

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Source rows containing both14

Distinct written forms14

Given-name readings11

Surname readings0

Adjacent 衣羅 forms8

Adjacent 羅衣 forms6

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

聖衣羅

Seira

せいら

2 source-recorded spellings in this reading group contain both 衣 and 羅Given name

実羅衣

Mirai

みらい

2 source-recorded spellings in this reading group contain both 衣 and 羅Given name

舞衣羅

Maira

まいら

2 source-recorded spellings in this reading group contain both 衣 and 羅Given name

亜衣羅

Aira

あいら

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

羅衣

Rai

らい

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

良衣羅

Raira

らいら

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

羅衣夢

Raimu

らいむ

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

羅衣菜

Raina

らいな

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

羅衣沙

Raisa

らいさ

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

芽衣羅

Meira

めいら

1 source-recorded spelling in this reading group contain both 衣 and 羅Given name

衣羅

Ira

いら

1 source-recorded spelling in this reading group contain both 衣 and 羅

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.