def rsi_dataframe(stock):
'''
Use this function in the API calling, takes the data we want from Alpha Vantage and saves it into a CSV.
Input:
stock = Name of ticker (i.e. 'TSLA' for Tesla stock).
Output:
csv dataframe.
'''
stock = stock
#api_key = '2KKOCMZP4P0O865A'
api_key = 'YVGW80PFI6I0ZH6Z'
period = 60
ts = TimeSeries(key=api_key, output_format='pandas')
data_ts = ts.get_daily_adjusted(stock.upper(), outputsize='full')
#indicator
ti = TechIndicators(key=api_key, output_format='pandas')
data_rsi = ti.get_rsi(symbol=stock.upper(),
interval='daily',
time_period=period,
series_type='close')
data_aroon = ti.get_aroon(symbol=stock.upper(),
interval='daily',
time_period=period)
data_mfi = ti.get_mfi(symbol=stock.upper(),
interval='daily',
time_period=period)
data_dx = ti.get_dx(symbol=stock.upper(),
interval='daily',
time_period=period)
#Get dfs removing unwanted lines.
df_adj_price = data_ts[0][period::]
df_rsi = data_rsi[0][period::]
df_aroon = data_aroon[0][period::]
df_mfi = data_mfi[0][period::]
df_dx = data_dx[0][period::]
#Merge all dfs into one.
df_adj_rsi = df_adj_price.merge(df_rsi, on='date')
df_aroon_mfi = df_aroon.merge(df_mfi, on='date')
df_1_2 = df_adj_rsi.merge(df_aroon_mfi, on='date')
df = df_1_2.merge(df_dx, on='date')
df.to_csv(str(stock))
def preds(api_key):
df = pd.read_csv('GOOGL.csv', index_col='Date')
preds = pd.DataFrame()
for i in np.arange(start=1, stop=6):
if preds.empty:
preds = pd.DataFrame(data=df['close'].pct_change(1))
preds.columns = ['today']
else:
lags = pd.DataFrame(df['close'].pct_change(i))
lags.columns = ['lag{}'.format(i)]
preds = preds.join(lags)
preds = preds.join(df['volume'])
preds = preds.join(df['close'])
preds['dir'] = (preds['close'] > preds['close'].shift(1)).shift(-1)
filename = 'GOOGL-lags.csv'
try:
preds.to_csv('{}'.format(filename))
print('GOOGL lags saved successfully as "{}"'.format(filename))
except:
print('Unable to save "{}"'.format(filename))
ti = TechIndicators(key=api_key, output_format='pandas')
sma, _ = ti.get_sma(symbol='GOOGL', interval='daily', series_type='close')
ema, _ = ti.get_ema(symbol='GOOGL', interval='daily', series_type='close')
wma, _ = ti.get_wma(symbol='GOOGL', interval='daily', series_type='close')
trima, _ = ti.get_trima(symbol='GOOGL',
interval='daily',
series_type='close')
kama, _ = ti.get_kama(symbol='GOOGL',
interval='daily',
series_type='close')
macd, _ = ti.get_macd(symbol='GOOGL',
interval='daily',
series_type='close')
rsi, _ = ti.get_rsi(symbol='GOOGL', interval='daily', series_type='close')
adx, _ = ti.get_adx(symbol='GOOGL', interval='daily')
apo, _ = ti.get_apo(symbol='GOOGL', interval='daily', series_type='close')
stoch, _ = ti.get_stoch(symbol='GOOGL', interval='daily')
ppo, _ = ti.get_ppo(symbol='GOOGL', interval='daily')
mom, _ = ti.get_mom(symbol='GOOGL', interval='daily', series_type='close')
cci, _ = ti.get_cci(symbol='GOOGL', interval='daily')
aroon, _ = ti.get_aroon(symbol='GOOGL',
interval='daily',
series_type='close')
mfi, _ = ti.get_mfi(symbol='GOOGL', interval='daily', series_type='close')
dx, _ = ti.get_dx(symbol='GOOGL', interval='daily', series_type='close')
ad, _ = ti.get_ad(symbol='GOOGL', interval='daily')
obv, _ = ti.get_obv(symbol='GOOGL', interval='daily')
filename2 = 'GOOGL-techs.csv'
try:
preds_test = pd.concat([
sma, ema, wma, trima, kama, macd, rsi, adx, apo, stoch, ppo, mom,
cci, aroon, mfi, dx, ad, obv
],
axis=1)
pd.DataFrame(preds_test).to_csv('{}'.format(filename2))
print('Google techs saved as successfully as "{}"'.format(filename2))
except:
print('Unable to save "{}"'.format(filename2))
def techIndicatorPull(symbol):
interval = "1min"
print("Calculating Tech Indicators ...")
ti = TechIndicators(key='1HAYLUHGCB6E0VXC', output_format='pandas')
print("Progress: 0% complete...")
ad_data, meta_data = ti.get_ad(symbol=symbol, interval=interval)
adosc_data, meta_data = ti.get_adosc(symbol=symbol, interval=interval)
adx_data, meta_data = ti.get_adx(symbol=symbol, interval=interval)
adxr_data, meta_data = ti.get_adxr(symbol=symbol, interval=interval)
apo_data, meta_data = ti.get_apo(symbol=symbol, interval=interval)
aroon_data, meta_data = ti.get_aroon(symbol=symbol, interval=interval)
aroonosc_data, meta_data = ti.get_aroonosc(symbol=symbol,
interval=interval)
atr_data, meta_data = ti.get_atr(symbol=symbol, interval=interval)
bop_data, meta_data = ti.get_bop(symbol=symbol, interval=interval)
cci_data, meta_data = ti.get_cci(symbol=symbol, interval=interval)
print("Progress: 20% complete...")
cmo_data, meta_data = ti.get_cmo(symbol=symbol, interval=interval)
dema_data, meta_data = ti.get_dema(symbol=symbol, interval=interval)
dx_data, meta_data = ti.get_dx(symbol=symbol, interval=interval)
ema_data, meta_data = ti.get_ema(symbol=symbol, interval=interval)
ht_dcperiod_data, meta_data = ti.get_ht_dcperiod(symbol=symbol,
interval=interval)
ht_dcphase_data, meta_data = ti.get_ht_dcphase(symbol=symbol,
interval=interval)
ht_phasor_data, meta_data = ti.get_ht_phasor(symbol=symbol,
interval=interval)
ht_sine_data, meta_data = ti.get_ht_sine(symbol=symbol, interval=interval)
ht_trendline_data, meta_data = ti.get_ht_trendline(symbol=symbol,
interval=interval)
ht_trendmode_data, meta_data = ti.get_ht_trendmode(symbol=symbol,
interval=interval)
print("Progress: 40% complete...")
kama_data, meta_data = ti.get_kama(symbol=symbol, interval=interval)
macd_data, meta_data = ti.get_macd(symbol=symbol, interval=interval)
macdext_data, meta_data = ti.get_macdext(symbol=symbol, interval=interval)
mama_data, meta_data = ti.get_mama(symbol=symbol, interval=interval)
mfi_data, meta_data = ti.get_mfi(symbol=symbol, interval=interval)
midpoint_data, meta_data = ti.get_midpoint(symbol=symbol,
interval=interval)
midprice_data, meta_data = ti.get_midprice(symbol=symbol,
interval=interval)
minus_di_data, meta_data = ti.get_minus_di(symbol=symbol,
interval=interval)
mom_data, meta_data = ti.get_mom(symbol=symbol, interval=interval)
natr_data, meta_data = ti.get_natr(symbol=symbol, interval=interval)
print("Progress: 60% complete...")
obv_data, meta_data = ti.get_obv(symbol=symbol, interval=interval)
plus_di_data, meta_data = ti.get_plus_di(symbol=symbol, interval=interval)
plus_dm_data, meta_data = ti.get_plus_dm(symbol=symbol, interval=interval)
ppo_data, meta_data = ti.get_ppo(symbol=symbol, interval=interval)
roc_data, meta_data = ti.get_roc(symbol=symbol, interval=interval)
rocr_data, meta_data = ti.get_rocr(symbol=symbol, interval=interval)
rsi_data, meta_data = ti.get_rsi(symbol=symbol, interval=interval)
sar_data, meta_data = ti.get_sar(symbol=symbol, interval=interval)
sma_data, meta_data = ti.get_sma(symbol=symbol, interval=interval)
stoch_data, meta_data = ti.get_stoch(symbol=symbol, interval=interval)
print("Progress: 80% complete...")
stochf_data, meta_data = ti.get_stochf(symbol=symbol, interval=interval)
stochrsi_data, meta_data = ti.get_stochrsi(symbol=symbol,
interval=interval)
t3_data, meta_data = ti.get_t3(symbol=symbol, interval=interval)
tema_data, meta_data = ti.get_tema(symbol=symbol, interval=interval)
trange_data, meta_data = ti.get_trange(symbol=symbol, interval=interval)
trima_data, meta_data = ti.get_trima(symbol=symbol, interval=interval)
trix_data, meta_data = ti.get_trix(symbol=symbol, interval=interval)
ultsoc_data, meta_data = ti.get_ultsoc(symbol=symbol, interval=interval)
willr_data, meta_data = ti.get_willr(symbol=symbol, interval=interval)
wma_data, meta_data = ti.get_wma(symbol=symbol, interval=interval)
bbands_data, meta_data = ti.get_bbands(symbol=symbol, interval=interval)
print("Progress: 90% complete...")
result = pd.concat([
ad_data, adosc_data, adx_data, adxr_data, apo_data, aroon_data,
aroonosc_data, atr_data, bop_data, cci_data, cmo_data, dema_data,
dx_data, ema_data, ht_dcperiod_data, ht_dcphase_data, ht_phasor_data,
ht_sine_data, ht_trendline_data, ht_trendmode_data, kama_data,
macd_data, macdext_data, mama_data, mfi_data, midpoint_data,
midprice_data, minus_di_data, mom_data, natr_data, obv_data,
plus_di_data, plus_dm_data, ppo_data, roc_data, rocr_data, rsi_data,
sar_data, sma_data, stoch_data, stochf_data, stochrsi_data, t3_data,
tema_data, trange_data, trima_data, trix_data, ultsoc_data, willr_data,
wma_data, bbands_data
],
axis=1)
result["stockticker"] = symbol
result = result.reindex(result.index.rename('timestamp'))
result = result.dropna(axis=0, how='any')
result = result.round(2)
result = result.rename(
columns={
'Chaikin A/D': 'ChaikinAD',
'Aroon Up': 'AroonUp',
'Aroon Down': 'AroonDown',
'LEAD SINE': 'LeadSine',
'Real Upper Band': 'RealUpperBand',
'Real Middle Band': 'RealMiddleBand',
'Real Lower Band': 'RealLowerBand'
})
fd = open('results/rawTechIndicatorData.csv', 'w')
result.to_csv(fd, index=True, encoding='utf-8')
fd.close()
print("Progress: 99% complete...")
df = pd.read_csv('results/rawTechIndicatorData.csv')
insertToOracleDatabase(
df,
'''insert /*+ ignore_row_on_dupkey_index(stocktechindicator, stocktechindicator_pk) */
into stocktechindicator
(timestamp,ChaikinAD,ADOSC,ADX,ADXR,
APO,AroonUp,AroonDown,AROONOSC,ATR,
BOP,CCI,CMO,DEMA,DX,
EMA,DCPERIOD,HT_DCPHASE,QUADRATURE, PHASE,
LEADSINE,SINE,HT_TRENDLINE,TRENDMODE,KAMA,
MACD,MACD_Hist,MACD_Signal,MACD_Signal2,MACD2,
MACD_Hist2,FAMA,MAMA,MFI,MIDPOINT,
MIDPRICE,MINUS_DI,MOM,NATR,OBV,
PLUS_DI,PLUS_DM,PPO,ROC,ROCR,
RSI,SAR,SMA,SlowK,SlowD,
FastK,FastD,FastK2,FastD2,T3,
TEMA,TRANGE,TRIMA,TRIX,ULTOSC,
WILLR,WMA,RealLowerBand,RealUpperBand,RealMiddleBand,
stockticker)
values (:1, :2, :3, :4, :5,
:6, :7, :8, :9, :10,
:11, :12, :13, :14, :15,
:16, :17, :18, :19, :20,
:21, :22, :23, :24, :25,
:26, :27, :28, :29, :30,
:31, :32, :33, :34, :35,
:36, :37, :38, :39, :40,
:41, :42, :43, :44, :45,
:46, :47, :48, :49, :50,
:51, :52, :53, :54, :55,
:56, :57, :58, :59, :60,
:61, :62, :63, :64, :65,
:66)''')
ad_data, meta_data = ti.get_ad(symbol=symbol, interval=interval)
adosc_data, meta_data = ti.get_adosc(symbol=symbol, interval=interval)
adx_data, meta_data = ti.get_adx(symbol=symbol, interval=interval)
adxr_data, meta_data = ti.get_adxr(symbol=symbol, interval=interval)
apo_data, meta_data = ti.get_apo(symbol=symbol, interval=interval)
aroon_data, meta_data = ti.get_aroon(symbol=symbol, interval=interval)
aroonosc_data, meta_data = ti.get_aroonosc(symbol=symbol, interval=interval)
atr_data, meta_data = ti.get_atr(symbol=symbol, interval=interval)
bop_data, meta_data = ti.get_bop(symbol=symbol, interval=interval)
cci_data, meta_data = ti.get_cci(symbol=symbol, interval=interval)
print("Progress: 20% complete...")
cmo_data, meta_data = ti.get_cmo(symbol=symbol, interval=interval)
dema_data, meta_data = ti.get_dema(symbol=symbol, interval=interval)
dx_data, meta_data = ti.get_dx(symbol=symbol, interval=interval)
ema_data, meta_data = ti.get_ema(symbol=symbol, interval=interval)
ht_dcperiod_data, meta_data = ti.get_ht_dcperiod(symbol=symbol, interval=interval)
ht_dcphase_data, meta_data = ti.get_ht_dcphase(symbol=symbol, interval=interval)
ht_phasor_data, meta_data = ti.get_ht_phasor(symbol=symbol, interval=interval)
ht_sine_data, meta_data = ti.get_ht_sine(symbol=symbol, interval=interval)
ht_trendline_data, meta_data = ti.get_ht_trendline(symbol=symbol, interval=interval)
ht_trendmode_data, meta_data = ti.get_ht_trendmode(symbol=symbol, interval=interval)
print("Progress: 40% complete...")
kama_data, meta_data = ti.get_kama(symbol=symbol, interval=interval)
macd_data, meta_data = ti.get_macd(symbol=symbol, interval=interval)
macdext_data, meta_data = ti.get_macdext(symbol=symbol, interval=interval)
mama_data, meta_data = ti.get_mama(symbol=symbol, interval=interval)
mfi_data, meta_data = ti.get_mfi(symbol=symbol, interval=interval)
def save_ti(ticker, interval='daily'):
ti = TechIndicators(key='WS8K5VM8FZL52BTH', output_format='pandas')
ti.get_sma(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_sma.csv')
call_check()
ti.get_ema(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ema.csv')
call_check()
ti.get_wma(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_wma.csv')
call_check()
ti.get_dema(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_dema.csv')
call_check()
ti.get_tema(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_tema.csv')
call_check()
ti.get_trima(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_trima.csv')
call_check()
ti.get_kama(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_kama.csv')
call_check()
ti.get_mama(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_mama.csv')
call_check()
ti.get_t3(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_t3.csv')
call_check()
ti.get_macd(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_macd.csv')
call_check()
ti.get_macdext(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_macdext.csv')
call_check()
ti.get_stoch(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_stoch.csv')
call_check()
ti.get_stochf(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_stochf.csv')
call_check()
ti.get_rsi(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_rsi.csv')
call_check()
ti.get_stochrsi(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_stochris.csv')
call_check()
ti.get_willr(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_willr.csv')
call_check()
ti.get_adx(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_adx.csv')
call_check()
ti.get_adxr(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_adxr.csv')
call_check()
ti.get_apo(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_apo.csv')
call_check()
ti.get_ppo(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ppo.csv')
call_check()
ti.get_mom(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_mom.csv')
call_check()
ti.get_bop(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_bop.csv')
call_check()
ti.get_cci(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_cci.csv')
call_check()
ti.get_cmo(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_cmo.csv')
call_check()
ti.get_roc(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_roc.csv')
call_check()
ti.get_rocr(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_rocr.csv')
call_check()
ti.get_aroon(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_aroon.csv')
call_check()
ti.get_aroonosc(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_aroonosc.csv')
call_check()
ti.get_mfi(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_mfi.csv')
call_check()
ti.get_trix(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_trix.csv')
call_check()
ti.get_ultosc(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ultosc.csv')
call_check()
ti.get_dx(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_dx.csv')
call_check()
ti.get_minus_di(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_minus_di.csv')
call_check()
ti.get_plus_di(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_plus_di.csv')
call_check()
ti.get_minus_dm(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_minus_dm.csv')
call_check()
ti.get_plus_dm(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_plus_dm.csv')
call_check()
ti.get_bbands(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_bbands.csv')
call_check()
ti.get_midpoint(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_midpoint.csv')
call_check()
ti.get_midprice(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_midprice.csv')
call_check()
ti.get_sar(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_sar.csv')
call_check()
ti.get_trange(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_trange.csv')
call_check()
ti.get_atr(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_atr.csv')
call_check()
ti.get_natr(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_natr.csv')
call_check()
ti.get_ad(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ad.csv')
call_check()
ti.get_adosc(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_adosc.csv')
call_check()
ti.get_obv(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_obv.csv')
call_check()
ti.get_ht_trendline(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_ht_trendline.csv')
call_check()
ti.get_ht_sine(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_ht_sine.csv')
call_check()
ti.get_ht_trendmode(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_ht_trendmode.csv')
call_check()
ti.get_ht_dcperiod(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_dcperiod.csv')
call_check()
ti.get_ht_dcphase(
ticker,
interval)[0].to_csv(f'./Stock Data/TI/{ticker}_{interval}_dcphase.csv')
call_check()
ti.get_ht_phasor(ticker, interval)[0].to_csv(
f'./Stock Data/TI/{ticker}_{interval}_ht_phasor.csv')
