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fix: partially SettingWithCopyWarning #235

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fix: partially SettingWithCopyWarning #235

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1 change: 1 addition & 0 deletions .circleci/config.yml
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -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: |
Expand Down
174 changes: 87 additions & 87 deletions ta/wrapper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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],
Expand All @@ -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],
Expand Down Expand Up @@ -168,46 +168,46 @@ 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()

# Bollinger Bands
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()

Expand Down Expand Up @@ -240,54 +240,54 @@ 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()

# Average Directional Movement Index (ADX)
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],
Expand All @@ -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()

Expand All @@ -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(
Expand All @@ -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],
Expand All @@ -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(
Expand All @@ -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,
Expand Down Expand Up @@ -405,25 +405,25 @@ 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()

# Stoch RSI (StochRSI)
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],
Expand All @@ -445,44 +445,44 @@ 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()

# Percentage Price Oscillator
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

Expand All @@ -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()

Expand Down