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.

苗

Jōyō · KANJIDIC grade 8 · 8 strokes

seedling, sapling, shoot

美

Jōyō · KANJIDIC grade 3 · 9 strokes

beauty, beautiful

Find exact-kanji names →

Source rows containing both11

Distinct written forms8

Given-name readings11

Surname readings0

Adjacent 苗美 forms4

Adjacent 美苗 forms3

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

真苗美

Manami

まなみ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

菜苗美

Nanami

ななみ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

美苗子

Minako

みなこ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

美苗

Mina

みな

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

苗美

Nami

なみ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

美苗

Misae

みさえ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

早苗美

Sanami

さなみ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

美苗

Minae

みなえ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

美苗文

Minamo

みなも

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

苗穂美

Nahomi

なほみ

1 source-recorded spelling in this reading group contain both 苗 and 美Given name

苗美

Naemi

なえみ

1 source-recorded spelling in this reading group contain both 苗 and 美

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.