CorpusStats

class scikitplot.corpus.CorpusStats(n_documents, n_tokens, n_chars, mean_tokens, median_tokens, min_tokens, max_tokens, language_counts, section_type_counts, source_type_counts, source_file_counts, collection_ids, has_embeddings, date_range)

Aggregate statistics over a CorpusDocument collection.

Parameters:

n_documentsint

Total document count.

n_tokensint

Total whitespace-delimited token count (sum of doc.word_count).

n_charsint

Total character count (sum of doc.char_count).

mean_tokensfloat

Average tokens per document. 0.0 when n_documents == 0.

median_tokensfloat

Median tokens per document. 0.0 when n_documents == 0.

min_tokensint

Minimum token count across documents.

max_tokensint

Maximum token count across documents.

language_countsdict[str, int]

Map of ISO 639-1 code → document count. None language stored as "unknown".

section_type_countsdict[str, int]

Map of SectionType.value → document count.

source_type_countsdict[str, int]

Map of SourceType.value → document count.

input_path_countsdict[str, int]

Map of input_path → document count.

collection_idslist[str]

Sorted unique collection_id values (None excluded).

has_embeddingsint

Number of documents where embedding is not None.

date_rangetuple[str, str] or None

(earliest, latest) source_date values, or None if no documents have dates.

Parameters:

• n_documents (int)

• n_tokens (int)

• n_chars (int)

• mean_tokens (float)

• median_tokens (float)

• min_tokens (int)

• max_tokens (int)

• language_counts (dict[str, int])

• section_type_counts (dict[str, int])

• source_type_counts (dict[str, int])

• source_file_counts (dict[str, int])

• collection_ids (list[str])

• has_embeddings (int)

• date_range (tuple[str, str] | None)

collection_ids: list[str]

date_range: tuple[str, str] | None

has_embeddings: int

language_counts: dict[str, int]

max_tokens: int

mean_tokens: float

median_tokens: float

min_tokens: int

n_chars: int

n_documents: int

n_tokens: int

section_type_counts: dict[str, int]

source_file_counts: dict[str, int]

source_type_counts: dict[str, int]

summary()

Return a human-readable one-page summary string.

Returns:

str

Return type:

str

to_dict()

Return a JSON-safe dictionary representation of the stats.

Returns:

dict[str, Any]

Return type:

dict[str, Any]