Search, industries, screener

Search

jfinance.Search(query, max_results=8, session=None, timeout=30, raise_errors=True)

Finds companies and funds by name or code.

Parameters

Name	Type	Default	Description
`query`	`str`	—	Company name, securities code or EDINET code
`max_results`	`int`	`8`	Maximum number of matches
`session`	`requests.Session`	`None`	Session to reuse
`timeout`	`int`	`30`	Seconds
`raise_errors`	`bool`	`True`	Raise on an HTTP error instead of returning empty

The remaining yfinance arguments — news_count, lists_count, include_research and the rest — are accepted and ignored, since EDINET carries none of that.

Attributes

Name	Type	Description
`quotes`	`list[dict]`	Matches, each with `symbol`, `shortname`, `longname`, `quoteType`, `exchange` and `score`
`all`	`dict`	`{"quotes": [...]}`. `news`, `lists` and `research` are absent
`response`	`dict`	The server response unchanged

jf.Search("トヨタ").quotes[0]["symbol"]     # '3116.T'

Lookup

jfinance.Lookup(query, session=None, timeout=30, raise_errors=True)

The same search in tabular form.

Methods

Method	Returns
`get_all(count=25)`	All matches
`get_stock(count=25)`	Equities
`get_etf(count=25)`	ETFs
`get_mutualfund(count=25)`	Investment trusts

all, stock, etf and mutualfund are the same, with the default count.

Returns — pandas.DataFrame, indexed by symbol, with columns shortName, quoteType, exchange and industryName.

Industries

Companies are classified under both Tokyo Stock Exchange schemes: TOPIX-17 sectors and the 33 TSE industries.

JpSector

jfinance.JpSector(key, session=None)

One TOPIX-17 sector.

Parameters

Name	Type	Description
`key`	`str`	Sector key, as in `"automobiles-transportation-equipment"`

Attributes

Name	Type	Description
`key`, `name`	`str`	Key and display name
`overview`	`dict`	`companiesCount`, `industriesCount` and `topCompaniesBasis`, which states how `top_companies` is ordered
`top_companies`	`pandas.DataFrame`	Listed companies in the sector. Columns `name`, `edinetCode`, `revenue`, `fiscalYear`
`industries`	`pandas.DataFrame`	TSE industries within the sector, indexed by `key`, with `name` and `companiesCount`

Static method

JpSector.all(session=None) -> pandas.DataFrame

All 17 sectors, indexed by key, with name, companiesCount and industriesCount.

JpIndustry

jfinance.JpIndustry(key, session=None)

One of the 33 TSE industries. key, name, overview and top_companies are as for JpSector; sector_key and sector_name give the TOPIX-17 sector it belongs to.

jf.JpIndustry("transportation-equipment").top_companies

top_companies is ordered by revenue in the latest fiscal year, consolidated where available. Since EDINET carries no share prices, this is not a ranking by market capitalisation.

Screener

edinet_screen

jfinance.edinet_screen(query, offset=None, size=None, sortField=None,
                       sortAsc=None, year=None, scope="consolidated",
                       session=None) -> dict

Filters companies on disclosed figures. Written the same way as yfinance’s screen.

Parameters

Name	Type	Default	Description
`query`	`EdinetQuery`	—	The condition
`offset`	`int`	`None`	Rows to skip
`size`	`int`	`None`	Rows to return
`sortField`	`str`	`None`	Field to sort by
`sortAsc`	`bool`	`None`	Ascending instead of descending
`year`	`int`	`None`	Fiscal year. Latest available when omitted
`scope`	`str`	`"consolidated"`	`"consolidated"` or `"standalone"`
`session`	`requests.Session`	`None`	Session to reuse

Returns — dict with start, count, total, fiscalYear, scope and quotes. Each entry in quotes carries symbol, shortName, longName, edinetCode, industry, sector, marketSegment, accountingStandard, fiscalYear, fiscalYearEnd, and the fields named in the query and in sortField.

jf.edinet_screen(
    jf.EdinetQuery("gt", ["roe", 0.2]),
    sortField="revenue",
    size=50,
)

EdinetQuery

jfinance.EdinetQuery(operator, operand)

Parameters

Name	Type	Description
`operator`	`str`	`"eq"`, `"is-in"`, `"btwn"`, `"gt"`, `"lt"`, `"gte"`, `"lte"`, `"and"`, `"or"`
`operand`	`list`	`[field, value]` for a comparison, or a list of `EdinetQuery` for `and` and `or`

q = jf.EdinetQuery("and", [
    jf.EdinetQuery("gt", ["roe", 0.15]),
    jf.EdinetQuery("is-in", ["sector", ["banks", "insurance"]]),
])
jf.edinet_screen(q)

Attributes

Name	Type	Description
`valid_fields`	`dict`	Fields that can be queried, grouped by category, each with its label and unit
`valid_values`	`dict`	Accepted values for the categorical fields
`to_dict()`	`dict`	The query as sent to the server

The field categories, and how many fields each holds:

Category	Fields	Examples
`pl`	19	`revenue`, `operatingIncome`, `ordinaryIncome`, `netIncome`, `grossProfit`
`bs`	8	`totalAssets`, `netAssets`, `capitalStock`, `bs_retainedEarnings`
`cf`	7	`operatingCF`, `investingCF`, `financingCF`, `capex`
`perShare`	5	`eps`, `epsDiluted`, `bps`, `dividendPerShare`
`ratio`	5	`roe`, `equityRatio`, `payoutRatio`, `per`, `tsr`
`shares`	1	`issuedShares`
`workforce`	2	`employees`, `temporaryEmployees`
`statement`	14	Bank and insurer items, as in `deposits`, `loans`, `net_premiums_written`
`categorical`	6	`sector`, `industry`, `market`, `listing`, `accountingStandard`, `fiscalMonth`

The accepted values for the categorical fields:

Field	Values
`market`	`prime`, `standard`, `growth`, `pro`
`listing`	`listed`, `unlisted`
`accountingStandard`	`Japan GAAP`, `IFRS`, `US GAAP`
`sector`, `industry`	The TOPIX-17 and TSE 33 keys
`fiscalMonth`	Month of the fiscal year end

Fields derived from share prices — market capitalisation, P/E, share price — are not available, since EDINET does not carry them. per is the price earnings ratio as stated in the annual report, not one calculated from a price.