def get_companies_per_country_in_sector(
sector: str, mktcap: str = "", exclude_exchanges: bool = True
):
"""Get number of companies per country in a specific sector (and specific market cap). [Source: Finance Database]
Parameters
----------
sector: str
Select sector to get number of companies by each country
mktcap: str
Select market cap of companies to consider from Small, Mid and Large
exclude_exchanges : bool
Exclude international exchanges
Returns
-------
dict
Dictionary of countries and number of companies in a specific sector
"""
companies_per_country = {}
for country in tqdm(get_countries(sector=sector)):
if country:
try:
companies = fd.select_equities(
sector=sector,
country=country,
exclude_exchanges=exclude_exchanges,
)
if mktcap:
companies = fd.search_products(
companies, query=mktcap + " Cap", search="market_cap"
)
companies_per_country[country] = len(companies)
except ValueError as e:
logger.exception(str(e))
return companies_per_country
def get_companies_per_sector_in_country(country: str,
mktcap: str = "",
exclude_exchanges: bool = True):
"""Get number of companies per sector in a specific country (and specific market cap). [Source: Finance Database]
Parameters
----------
country: str
Select country to get number of companies by each sector
mktcap: str
Select market cap of companies to consider from Small, Mid and Large
exclude_exchanges : bool
Exclude international exchanges
Returns
-------
dict
Dictionary of sectors and number of companies in a specific country
"""
companies_per_sector = {}
for sector in tqdm(get_sectors(country=country)):
if sector:
try:
companies = fd.select_equities(
country=country,
sector=sector,
exclude_exchanges=exclude_exchanges)
if mktcap:
companies = fd.search_products(companies,
query=mktcap + " Cap",
search="market_cap")
companies_per_sector[sector] = len(companies)
except ValueError:
pass
return companies_per_sector
def show_equities(
country: str,
sector: str,
industry: str,
name: str,
description: str,
marketcap: str,
amount: int,
include_exchanges: bool,
options: str,
):
"""
Display a selection of Equities based on country, sector, industry, name and/or description filtered
by market cap. If no arguments are given, return equities categorized as Large Cap.
[Source: Finance Database]
Parameters
----------
country: str
Search by country to find stocks matching the criteria.
sector : str
Search by sector to find stocks matching the criteria.
industry : str
Search by industry to find stocks matching the criteria.
name : str
Search by name to find stocks matching the criteria.
description : str
Search by description to find stocks matching the criteria.
marketcap : str
Select stocks based on the market cap.
amount : int
Number of stocks to display, default is 10.
include_exchanges: bool
When you wish to include different exchanges use this boolean.
options : str
Show the country, sector or industry options.
"""
if options is not None:
for option in fd.show_options("equities", options):
print(option)
return
if country is not None:
country = " ".join(country).title()
if sector is not None:
sector = " ".join(sector).title()
if industry is not None:
industry = " ".join(industry).title()
data = fd.select_equities(
country=country,
sector=sector,
industry=industry,
exclude_exchanges=include_exchanges,
)
if name is not None:
data = fd.search_products(data, query=" ".join(name), search="long_name")
if description is not None:
data = fd.search_products(data, query=" ".join(description), search="summary")
if marketcap is not None:
data = fd.search_products(
data, query=f"{''.join(marketcap)} Cap", search="market_cap"
)
tabulate_data = pd.DataFrame(data).T[
[
"long_name",
"sector",
"industry",
"country",
"city",
"website",
"market_cap",
]
]
if gtff.USE_TABULATE_DF:
print(
tabulate(
tabulate_data.iloc[:amount],
showindex=True,
headers=[
"Name",
"Sector",
"Industry",
"Country",
"City",
"Website",
"Market Cap",
],
floatfmt=".2f",
tablefmt="fancy_grid",
),
"\n",
)
else:
print(tabulate_data.iloc[:amount].to_string(), "\n")
def filter_stocks(
country: str,
sector: str,
industry: str,
marketcap: str = "",
exclude_exchanges: bool = True,
):
"""Filter stocks based on country, sector, industry, market cap and exclude exchanges. [Source: Finance Database]
Parameters
----------
country: str
Search by country to find stocks matching the criteria.
sector : str
Search by sector to find stocks matching the criteria.
industry : str
Search by industry to find stocks matching the criteria.
marketcap : str
Select stocks based on the market cap.
exclude_exchanges: bool
When you wish to include different exchanges use this boolean.
Returns
-------
list
List of filtered stocks
"""
try:
if country:
if sector:
if industry:
data = fd.select_equities(
country=country,
sector=sector,
industry=industry,
exclude_exchanges=exclude_exchanges,
)
else: # no industry
data = fd.select_equities(
country=country,
sector=sector,
exclude_exchanges=exclude_exchanges,
)
else: # no sector
if industry:
data = fd.select_equities(
country=country,
industry=industry,
exclude_exchanges=exclude_exchanges,
)
else: # no industry
data = fd.select_equities(
country=country,
exclude_exchanges=exclude_exchanges,
)
else: # no country
if sector:
if industry:
data = fd.select_equities(
sector=sector,
industry=industry,
exclude_exchanges=exclude_exchanges,
)
else: # no industry
data = fd.select_equities(
sector=sector,
exclude_exchanges=exclude_exchanges,
)
else: # no sector
if industry:
data = fd.select_equities(
industry=industry,
exclude_exchanges=exclude_exchanges,
)
else: # no industry
data = {}
if marketcap:
data = fd.search_products(data,
query=marketcap,
search="market_cap")
return list(data.keys())
except ValueError:
return list()
