From 7db4c3cc7dc9e6a1b1e7c8ca1dfbc750162a97a4 Mon Sep 17 00:00:00 2001 From: Patrik Lermon Date: Fri, 2 Apr 2021 20:27:36 +0200 Subject: [PATCH] fix: partially SettingWithCopyWarning --- .circleci/config.yml | 1 + ta/wrapper.py | 174 +++++++++++++++++++++---------------------- 2 files changed, 88 insertions(+), 87 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 11bbc528..70ef7acd 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -14,6 +14,7 @@ jobs: python3 -m venv venv . venv/bin/activate pip install -r requirements-test.txt + pip install pycodestyle - run: name: Run linter command: | diff --git a/ta/wrapper.py b/ta/wrapper.py index fefd8591..f0952d37 100644 --- a/ta/wrapper.py +++ b/ta/wrapper.py @@ -86,27 +86,27 @@ def add_volume_ta( """ # Accumulation Distribution Index - df[f"{colprefix}volume_adi"] = AccDistIndexIndicator( + df.loc[f"{colprefix}volume_adi"] = AccDistIndexIndicator( high=df[high], low=df[low], close=df[close], volume=df[volume], fillna=fillna ).acc_dist_index() # On Balance Volume - df[f"{colprefix}volume_obv"] = OnBalanceVolumeIndicator( + df.loc[f"{colprefix}volume_obv"] = OnBalanceVolumeIndicator( close=df[close], volume=df[volume], fillna=fillna ).on_balance_volume() # Chaikin Money Flow - df[f"{colprefix}volume_cmf"] = ChaikinMoneyFlowIndicator( + df.loc[f"{colprefix}volume_cmf"] = ChaikinMoneyFlowIndicator( high=df[high], low=df[low], close=df[close], volume=df[volume], fillna=fillna ).chaikin_money_flow() # Force Index - df[f"{colprefix}volume_fi"] = ForceIndexIndicator( + df.loc[f"{colprefix}volume_fi"] = ForceIndexIndicator( close=df[close], volume=df[volume], window=13, fillna=fillna ).force_index() # Money Flow Indicator - df[f"{colprefix}volume_mfi"] = MFIIndicator( + df.loc[f"{colprefix}volume_mfi"] = MFIIndicator( high=df[high], low=df[low], close=df[close], @@ -119,21 +119,21 @@ def add_volume_ta( indicator_eom = EaseOfMovementIndicator( high=df[high], low=df[low], volume=df[volume], window=14, fillna=fillna ) - df[f"{colprefix}volume_em"] = indicator_eom.ease_of_movement() - df[f"{colprefix}volume_sma_em"] = indicator_eom.sma_ease_of_movement() + df.loc[f"{colprefix}volume_em"] = indicator_eom.ease_of_movement() + df.loc[f"{colprefix}volume_sma_em"] = indicator_eom.sma_ease_of_movement() # Volume Price Trend - df[f"{colprefix}volume_vpt"] = VolumePriceTrendIndicator( + df.loc[f"{colprefix}volume_vpt"] = VolumePriceTrendIndicator( close=df[close], volume=df[volume], fillna=fillna ).volume_price_trend() # Negative Volume Index - df[f"{colprefix}volume_nvi"] = NegativeVolumeIndexIndicator( + df.loc[f"{colprefix}volume_nvi"] = NegativeVolumeIndexIndicator( close=df[close], volume=df[volume], fillna=fillna ).negative_volume_index() # Volume Weighted Average Price - df[f"{colprefix}volume_vwap"] = VolumeWeightedAveragePrice( + df.loc[f"{colprefix}volume_vwap"] = VolumeWeightedAveragePrice( high=df[high], low=df[low], close=df[close], @@ -168,7 +168,7 @@ def add_volatility_ta( """ # Average True Range - df[f"{colprefix}volatility_atr"] = AverageTrueRange( + df.loc[f"{colprefix}volatility_atr"] = AverageTrueRange( close=df[close], high=df[high], low=df[low], window=10, fillna=fillna ).average_true_range() @@ -176,38 +176,38 @@ def add_volatility_ta( indicator_bb = BollingerBands( close=df[close], window=20, window_dev=2, fillna=fillna ) - df[f"{colprefix}volatility_bbm"] = indicator_bb.bollinger_mavg() - df[f"{colprefix}volatility_bbh"] = indicator_bb.bollinger_hband() - df[f"{colprefix}volatility_bbl"] = indicator_bb.bollinger_lband() - df[f"{colprefix}volatility_bbw"] = indicator_bb.bollinger_wband() - df[f"{colprefix}volatility_bbp"] = indicator_bb.bollinger_pband() - df[f"{colprefix}volatility_bbhi"] = indicator_bb.bollinger_hband_indicator() - df[f"{colprefix}volatility_bbli"] = indicator_bb.bollinger_lband_indicator() + df.loc[f"{colprefix}volatility_bbm"] = indicator_bb.bollinger_mavg() + df.loc[f"{colprefix}volatility_bbh"] = indicator_bb.bollinger_hband() + df.loc[f"{colprefix}volatility_bbl"] = indicator_bb.bollinger_lband() + df.loc[f"{colprefix}volatility_bbw"] = indicator_bb.bollinger_wband() + df.loc[f"{colprefix}volatility_bbp"] = indicator_bb.bollinger_pband() + df.loc[f"{colprefix}volatility_bbhi"] = indicator_bb.bollinger_hband_indicator() + df.loc[f"{colprefix}volatility_bbli"] = indicator_bb.bollinger_lband_indicator() # Keltner Channel indicator_kc = KeltnerChannel( close=df[close], high=df[high], low=df[low], window=10, fillna=fillna ) - df[f"{colprefix}volatility_kcc"] = indicator_kc.keltner_channel_mband() - df[f"{colprefix}volatility_kch"] = indicator_kc.keltner_channel_hband() - df[f"{colprefix}volatility_kcl"] = indicator_kc.keltner_channel_lband() - df[f"{colprefix}volatility_kcw"] = indicator_kc.keltner_channel_wband() - df[f"{colprefix}volatility_kcp"] = indicator_kc.keltner_channel_pband() - df[f"{colprefix}volatility_kchi"] = indicator_kc.keltner_channel_hband_indicator() - df[f"{colprefix}volatility_kcli"] = indicator_kc.keltner_channel_lband_indicator() + df.loc[f"{colprefix}volatility_kcc"] = indicator_kc.keltner_channel_mband() + df.loc[f"{colprefix}volatility_kch"] = indicator_kc.keltner_channel_hband() + df.loc[f"{colprefix}volatility_kcl"] = indicator_kc.keltner_channel_lband() + df.loc[f"{colprefix}volatility_kcw"] = indicator_kc.keltner_channel_wband() + df.loc[f"{colprefix}volatility_kcp"] = indicator_kc.keltner_channel_pband() + df.loc[f"{colprefix}volatility_kchi"] = indicator_kc.keltner_channel_hband_indicator() + df.loc[f"{colprefix}volatility_kcli"] = indicator_kc.keltner_channel_lband_indicator() # Donchian Channel indicator_dc = DonchianChannel( high=df[high], low=df[low], close=df[close], window=20, offset=0, fillna=fillna ) - df[f"{colprefix}volatility_dcl"] = indicator_dc.donchian_channel_lband() - df[f"{colprefix}volatility_dch"] = indicator_dc.donchian_channel_hband() - df[f"{colprefix}volatility_dcm"] = indicator_dc.donchian_channel_mband() - df[f"{colprefix}volatility_dcw"] = indicator_dc.donchian_channel_wband() - df[f"{colprefix}volatility_dcp"] = indicator_dc.donchian_channel_pband() + df.loc[f"{colprefix}volatility_dcl"] = indicator_dc.donchian_channel_lband() + df.loc[f"{colprefix}volatility_dch"] = indicator_dc.donchian_channel_hband() + df.loc[f"{colprefix}volatility_dcm"] = indicator_dc.donchian_channel_mband() + df.loc[f"{colprefix}volatility_dcw"] = indicator_dc.donchian_channel_wband() + df.loc[f"{colprefix}volatility_dcp"] = indicator_dc.donchian_channel_pband() # Ulcer Index - df[f"{colprefix}volatility_ui"] = UlcerIndex( + df.loc[f"{colprefix}volatility_ui"] = UlcerIndex( close=df[close], window=14, fillna=fillna ).ulcer_index() @@ -240,23 +240,23 @@ def add_trend_ta( indicator_macd = MACD( close=df[close], window_slow=26, window_fast=12, window_sign=9, fillna=fillna ) - df[f"{colprefix}trend_macd"] = indicator_macd.macd() - df[f"{colprefix}trend_macd_signal"] = indicator_macd.macd_signal() - df[f"{colprefix}trend_macd_diff"] = indicator_macd.macd_diff() + df.loc[f"{colprefix}trend_macd"] = indicator_macd.macd() + df.loc[f"{colprefix}trend_macd_signal"] = indicator_macd.macd_signal() + df.loc[f"{colprefix}trend_macd_diff"] = indicator_macd.macd_diff() # SMAs - df[f"{colprefix}trend_sma_fast"] = SMAIndicator( + df.loc[f"{colprefix}trend_sma_fast"] = SMAIndicator( close=df[close], window=12, fillna=fillna ).sma_indicator() - df[f"{colprefix}trend_sma_slow"] = SMAIndicator( + df.loc[f"{colprefix}trend_sma_slow"] = SMAIndicator( close=df[close], window=26, fillna=fillna ).sma_indicator() # EMAs - df[f"{colprefix}trend_ema_fast"] = EMAIndicator( + df.loc[f"{colprefix}trend_ema_fast"] = EMAIndicator( close=df[close], window=12, fillna=fillna ).ema_indicator() - df[f"{colprefix}trend_ema_slow"] = EMAIndicator( + df.loc[f"{colprefix}trend_ema_slow"] = EMAIndicator( close=df[close], window=26, fillna=fillna ).ema_indicator() @@ -264,30 +264,30 @@ def add_trend_ta( indicator_adx = ADXIndicator( high=df[high], low=df[low], close=df[close], window=14, fillna=fillna ) - df[f"{colprefix}trend_adx"] = indicator_adx.adx() - df[f"{colprefix}trend_adx_pos"] = indicator_adx.adx_pos() - df[f"{colprefix}trend_adx_neg"] = indicator_adx.adx_neg() + df.loc[f"{colprefix}trend_adx"] = indicator_adx.adx() + df.loc[f"{colprefix}trend_adx_pos"] = indicator_adx.adx_pos() + df.loc[f"{colprefix}trend_adx_neg"] = indicator_adx.adx_neg() # Vortex Indicator indicator_vortex = VortexIndicator( high=df[high], low=df[low], close=df[close], window=14, fillna=fillna ) - df[f"{colprefix}trend_vortex_ind_pos"] = indicator_vortex.vortex_indicator_pos() - df[f"{colprefix}trend_vortex_ind_neg"] = indicator_vortex.vortex_indicator_neg() - df[f"{colprefix}trend_vortex_ind_diff"] = indicator_vortex.vortex_indicator_diff() + df.loc[f"{colprefix}trend_vortex_ind_pos"] = indicator_vortex.vortex_indicator_pos() + df.loc[f"{colprefix}trend_vortex_ind_neg"] = indicator_vortex.vortex_indicator_neg() + df.loc[f"{colprefix}trend_vortex_ind_diff"] = indicator_vortex.vortex_indicator_diff() # TRIX Indicator - df[f"{colprefix}trend_trix"] = TRIXIndicator( + df.loc[f"{colprefix}trend_trix"] = TRIXIndicator( close=df[close], window=15, fillna=fillna ).trix() # Mass Index - df[f"{colprefix}trend_mass_index"] = MassIndex( + df.loc[f"{colprefix}trend_mass_index"] = MassIndex( high=df[high], low=df[low], window_fast=9, window_slow=25, fillna=fillna ).mass_index() # CCI Indicator - df[f"{colprefix}trend_cci"] = CCIIndicator( + df.loc[f"{colprefix}trend_cci"] = CCIIndicator( high=df[high], low=df[low], close=df[close], @@ -297,7 +297,7 @@ def add_trend_ta( ).cci() # DPO Indicator - df[f"{colprefix}trend_dpo"] = DPOIndicator( + df.loc[f"{colprefix}trend_dpo"] = DPOIndicator( close=df[close], window=20, fillna=fillna ).dpo() @@ -315,9 +315,9 @@ def add_trend_ta( nsig=9, fillna=fillna, ) - df[f"{colprefix}trend_kst"] = indicator_kst.kst() - df[f"{colprefix}trend_kst_sig"] = indicator_kst.kst_sig() - df[f"{colprefix}trend_kst_diff"] = indicator_kst.kst_diff() + df.loc[f"{colprefix}trend_kst"] = indicator_kst.kst() + df.loc[f"{colprefix}trend_kst_sig"] = indicator_kst.kst_sig() + df.loc[f"{colprefix}trend_kst_diff"] = indicator_kst.kst_diff() # Ichimoku Indicator indicator_ichi = IchimokuIndicator( @@ -329,10 +329,10 @@ def add_trend_ta( visual=False, fillna=fillna, ) - df[f"{colprefix}trend_ichimoku_conv"] = indicator_ichi.ichimoku_conversion_line() - df[f"{colprefix}trend_ichimoku_base"] = indicator_ichi.ichimoku_base_line() - df[f"{colprefix}trend_ichimoku_a"] = indicator_ichi.ichimoku_a() - df[f"{colprefix}trend_ichimoku_b"] = indicator_ichi.ichimoku_b() + df.loc[f"{colprefix}trend_ichimoku_conv"] = indicator_ichi.ichimoku_conversion_line() + df.loc[f"{colprefix}trend_ichimoku_base"] = indicator_ichi.ichimoku_base_line() + df.loc[f"{colprefix}trend_ichimoku_a"] = indicator_ichi.ichimoku_a() + df.loc[f"{colprefix}trend_ichimoku_b"] = indicator_ichi.ichimoku_b() indicator_ichi_visual = IchimokuIndicator( high=df[high], low=df[low], @@ -342,14 +342,14 @@ def add_trend_ta( visual=True, fillna=fillna, ) - df[f"{colprefix}trend_visual_ichimoku_a"] = indicator_ichi_visual.ichimoku_a() - df[f"{colprefix}trend_visual_ichimoku_b"] = indicator_ichi_visual.ichimoku_b() + df.loc[f"{colprefix}trend_visual_ichimoku_a"] = indicator_ichi_visual.ichimoku_a() + df.loc[f"{colprefix}trend_visual_ichimoku_b"] = indicator_ichi_visual.ichimoku_b() # Aroon Indicator indicator_aroon = AroonIndicator(close=df[close], window=25, fillna=fillna) - df[f"{colprefix}trend_aroon_up"] = indicator_aroon.aroon_up() - df[f"{colprefix}trend_aroon_down"] = indicator_aroon.aroon_down() - df[f"{colprefix}trend_aroon_ind"] = indicator_aroon.aroon_indicator() + df.loc[f"{colprefix}trend_aroon_up"] = indicator_aroon.aroon_up() + df.loc[f"{colprefix}trend_aroon_down"] = indicator_aroon.aroon_down() + df.loc[f"{colprefix}trend_aroon_ind"] = indicator_aroon.aroon_indicator() # PSAR Indicator indicator_psar = PSARIndicator( @@ -360,14 +360,14 @@ def add_trend_ta( max_step=0.20, fillna=fillna, ) - # df[f'{colprefix}trend_psar'] = indicator.psar() - df[f"{colprefix}trend_psar_up"] = indicator_psar.psar_up() - df[f"{colprefix}trend_psar_down"] = indicator_psar.psar_down() - df[f"{colprefix}trend_psar_up_indicator"] = indicator_psar.psar_up_indicator() - df[f"{colprefix}trend_psar_down_indicator"] = indicator_psar.psar_down_indicator() + # df.loc[f'{colprefix}trend_psar'] = indicator.psar() + df.loc[f"{colprefix}trend_psar_up"] = indicator_psar.psar_up() + df.loc[f"{colprefix}trend_psar_down"] = indicator_psar.psar_down() + df.loc[f"{colprefix}trend_psar_up_indicator"] = indicator_psar.psar_up_indicator() + df.loc[f"{colprefix}trend_psar_down_indicator"] = indicator_psar.psar_down_indicator() # Schaff Trend Cycle (STC) - df[f"{colprefix}trend_stc"] = STCIndicator( + df.loc[f"{colprefix}trend_stc"] = STCIndicator( close=df[close], window_slow=50, window_fast=23, @@ -405,7 +405,7 @@ def add_momentum_ta( """ # Relative Strength Index (RSI) - df[f"{colprefix}momentum_rsi"] = RSIIndicator( + df.loc[f"{colprefix}momentum_rsi"] = RSIIndicator( close=df[close], window=14, fillna=fillna ).rsi() @@ -413,17 +413,17 @@ def add_momentum_ta( indicator_srsi = StochRSIIndicator( close=df[close], window=14, smooth1=3, smooth2=3, fillna=fillna ) - df[f"{colprefix}momentum_stoch_rsi"] = indicator_srsi.stochrsi() - df[f"{colprefix}momentum_stoch_rsi_k"] = indicator_srsi.stochrsi_k() - df[f"{colprefix}momentum_stoch_rsi_d"] = indicator_srsi.stochrsi_d() + df.loc[f"{colprefix}momentum_stoch_rsi"] = indicator_srsi.stochrsi() + df.loc[f"{colprefix}momentum_stoch_rsi_k"] = indicator_srsi.stochrsi_k() + df.loc[f"{colprefix}momentum_stoch_rsi_d"] = indicator_srsi.stochrsi_d() # TSI Indicator - df[f"{colprefix}momentum_tsi"] = TSIIndicator( + df.loc[f"{colprefix}momentum_tsi"] = TSIIndicator( close=df[close], window_slow=25, window_fast=13, fillna=fillna ).tsi() # Ultimate Oscillator - df[f"{colprefix}momentum_uo"] = UltimateOscillator( + df.loc[f"{colprefix}momentum_uo"] = UltimateOscillator( high=df[high], low=df[low], close=df[close], @@ -445,26 +445,26 @@ def add_momentum_ta( smooth_window=3, fillna=fillna, ) - df[f"{colprefix}momentum_stoch"] = indicator_so.stoch() - df[f"{colprefix}momentum_stoch_signal"] = indicator_so.stoch_signal() + df.loc[f"{colprefix}momentum_stoch"] = indicator_so.stoch() + df.loc[f"{colprefix}momentum_stoch_signal"] = indicator_so.stoch_signal() # Williams R Indicator - df[f"{colprefix}momentum_wr"] = WilliamsRIndicator( + df.loc[f"{colprefix}momentum_wr"] = WilliamsRIndicator( high=df[high], low=df[low], close=df[close], lbp=14, fillna=fillna ).williams_r() # Awesome Oscillator - df[f"{colprefix}momentum_ao"] = AwesomeOscillatorIndicator( + df.loc[f"{colprefix}momentum_ao"] = AwesomeOscillatorIndicator( high=df[high], low=df[low], window1=5, window2=34, fillna=fillna ).awesome_oscillator() # KAMA - df[f"{colprefix}momentum_kama"] = KAMAIndicator( + df.loc[f"{colprefix}momentum_kama"] = KAMAIndicator( close=df[close], window=10, pow1=2, pow2=30, fillna=fillna ).kama() # Rate Of Change - df[f"{colprefix}momentum_roc"] = ROCIndicator( + df.loc[f"{colprefix}momentum_roc"] = ROCIndicator( close=df[close], window=12, fillna=fillna ).roc() @@ -472,17 +472,17 @@ def add_momentum_ta( indicator_ppo = PercentagePriceOscillator( close=df[close], window_slow=26, window_fast=12, window_sign=9, fillna=fillna ) - df[f"{colprefix}momentum_ppo"] = indicator_ppo.ppo() - df[f"{colprefix}momentum_ppo_signal"] = indicator_ppo.ppo_signal() - df[f"{colprefix}momentum_ppo_hist"] = indicator_ppo.ppo_hist() + df.loc[f"{colprefix}momentum_ppo"] = indicator_ppo.ppo() + df.loc[f"{colprefix}momentum_ppo_signal"] = indicator_ppo.ppo_signal() + df.loc[f"{colprefix}momentum_ppo_hist"] = indicator_ppo.ppo_hist() # Percentage Volume Oscillator indicator_pvo = PercentageVolumeOscillator( volume=df[volume], window_slow=26, window_fast=12, window_sign=9, fillna=fillna ) - df[f"{colprefix}momentum_ppo"] = indicator_pvo.pvo() - df[f"{colprefix}momentum_ppo_signal"] = indicator_pvo.pvo_signal() - df[f"{colprefix}momentum_ppo_hist"] = indicator_pvo.pvo_hist() + df.loc[f"{colprefix}momentum_ppo"] = indicator_pvo.pvo() + df.loc[f"{colprefix}momentum_ppo_signal"] = indicator_pvo.pvo_signal() + df.loc[f"{colprefix}momentum_ppo_hist"] = indicator_pvo.pvo_hist() return df @@ -502,17 +502,17 @@ def add_others_ta( pandas.core.frame.DataFrame: Dataframe with new features. """ # Daily Return - df[f"{colprefix}others_dr"] = DailyReturnIndicator( + df.loc[f"{colprefix}others_dr"] = DailyReturnIndicator( close=df[close], fillna=fillna ).daily_return() # Daily Log Return - df[f"{colprefix}others_dlr"] = DailyLogReturnIndicator( + df.loc[f"{colprefix}others_dlr"] = DailyLogReturnIndicator( close=df[close], fillna=fillna ).daily_log_return() # Cumulative Return - df[f"{colprefix}others_cr"] = CumulativeReturnIndicator( + df.loc[f"{colprefix}others_cr"] = CumulativeReturnIndicator( close=df[close], fillna=fillna ).cumulative_return()