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numerai-signals-tickermap's Issues

Lions Gate Entertainment (LGF)

Original: LGF.A, LGF/A US ,LGF-A.TO
Corrected: LGF.A ,LGF/A US, LGF-A
Note: Drop .TO suffix from the ticker

Original: LGF.B, LGF/B US, LFG-B.To
Corrected: LGF.B, LGF/B US, LGF-B
Note: Drop .TO suffix from ticker and correct Yahoo spelling (LFG to LGF)

full mapping completed

I've mapped bloomberg to Alpha Vantage using the following code:

napi = numerapi.SignalsAPI(NAPI_PUBLIC_KEY, NAPI_PRIVATE_KEY)
eligible_tickers = pd.DataFrame(napi.ticker_universe())
eligible_tickers.columns = ['bloomberg_ticker']
eligible_tickers = eligible_tickers.iloc[1:, :].copy()
eligible_tickers['ticker'] = eligible_tickers.bloomberg_ticker.str[:-3]

reduced_tickers = eligible_tickers[(eligible_tickers.bloomberg_ticker.str.contains(" PW") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" CP") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" TB") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" HB") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" IT") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" ID") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" PM") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" SP") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" FH") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" AV") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" GA") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" DC") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" NZ") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" TI") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" NO") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" SM") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" IJ") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" MF") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" SJ") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" AU") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" SW") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" SS") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" KS") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" MK") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" IM") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" JP") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" TT") == False)&\
(eligible_tickers.bloomberg_ticker.str.contains(" HK") == False)].copy()
reduced_tickers['av_ticker'] = 1
reduced_tickers['av_ticker'] = np.where(reduced_tickers.bloomberg_ticker.str.contains(" US"), reduced_tickers.ticker,
np.where(reduced_tickers.bloomberg_ticker.str.contains(" NA"), reduced_tickers.ticker + ".AMS",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" CA"), reduced_tickers.ticker + ".TRT",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" BB"), reduced_tickers.ticker + ".BRU",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" FP"), reduced_tickers.ticker + ".PAR",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" GR"), reduced_tickers.ticker + ".DEX",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" PL"), reduced_tickers.ticker + ".LIS",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" LN"), reduced_tickers.ticker + ".LON",
np.where(reduced_tickers.bloomberg_ticker.str.contains(" BZ"), reduced_tickers.ticker + ".SAO", reduced_tickers.av_ticker)))))))))
reduced_tickers['av_ticker'] = np.where(reduced_tickers.av_ticker.str.endswith("/A.LON"), reduced_tickers.av_ticker.str.replace("/", "-"), reduced_tickers.av_ticker)
reduced_tickers['av_ticker'] = np.where(reduced_tickers.av_ticker.str.endswith("LON"), reduced_tickers.av_ticker.str.replace("/", ""), reduced_tickers.av_ticker)
reduced_tickers['av_ticker'] = np.where(reduced_tickers.av_ticker.str.endswith("LON"), reduced_tickers.av_ticker.str.replace("*", ""), reduced_tickers.av_ticker)
reduced_tickers['av_ticker'] = reduced_tickers.av_ticker.str.replace("/", "-")
####ticker name changes should be handled by NUMERAI prior to releasing the weekly eligible ticker list####

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